Add files using upload-large-folder tool

.gitattributes

@@ -1,60 +1,2 @@
-*.7z filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
-*.avro filter=lfs diff=lfs merge=lfs -text
-*.bin filter=lfs diff=lfs merge=lfs -text
-*.bz2 filter=lfs diff=lfs merge=lfs -text
-*.ckpt filter=lfs diff=lfs merge=lfs -text
-*.ftz filter=lfs diff=lfs merge=lfs -text
-*.gz filter=lfs diff=lfs merge=lfs -text
-*.h5 filter=lfs diff=lfs merge=lfs -text
-*.joblib filter=lfs diff=lfs merge=lfs -text
-*.lfs.* filter=lfs diff=lfs merge=lfs -text
-*.lz4 filter=lfs diff=lfs merge=lfs -text
-*.mds filter=lfs diff=lfs merge=lfs -text
-*.mlmodel filter=lfs diff=lfs merge=lfs -text
-*.model filter=lfs diff=lfs merge=lfs -text
-*.msgpack filter=lfs diff=lfs merge=lfs -text
-*.npy filter=lfs diff=lfs merge=lfs -text
-*.npz filter=lfs diff=lfs merge=lfs -text
-*.onnx filter=lfs diff=lfs merge=lfs -text
-*.ot filter=lfs diff=lfs merge=lfs -text
-*.parquet filter=lfs diff=lfs merge=lfs -text
-*.pb filter=lfs diff=lfs merge=lfs -text
-*.pickle filter=lfs diff=lfs merge=lfs -text
-*.pkl filter=lfs diff=lfs merge=lfs -text
-*.pt filter=lfs diff=lfs merge=lfs -text
-*.pth filter=lfs diff=lfs merge=lfs -text
-*.rar filter=lfs diff=lfs merge=lfs -text
-*.safetensors filter=lfs diff=lfs merge=lfs -text
-saved_model/**/* filter=lfs diff=lfs merge=lfs -text
-*.tar.* filter=lfs diff=lfs merge=lfs -text
-*.tar filter=lfs diff=lfs merge=lfs -text
-*.tflite filter=lfs diff=lfs merge=lfs -text
-*.tgz filter=lfs diff=lfs merge=lfs -text
-*.wasm filter=lfs diff=lfs merge=lfs -text
-*.xz filter=lfs diff=lfs merge=lfs -text
-*.zip filter=lfs diff=lfs merge=lfs -text
-*.zst filter=lfs diff=lfs merge=lfs -text
-*tfevents* filter=lfs diff=lfs merge=lfs -text
-# Audio files - uncompressed
-*.pcm filter=lfs diff=lfs merge=lfs -text
-*.sam filter=lfs diff=lfs merge=lfs -text
-*.raw filter=lfs diff=lfs merge=lfs -text
-# Audio files - compressed
-*.aac filter=lfs diff=lfs merge=lfs -text
-*.flac filter=lfs diff=lfs merge=lfs -text
-*.mp3 filter=lfs diff=lfs merge=lfs -text
-*.ogg filter=lfs diff=lfs merge=lfs -text
-*.wav filter=lfs diff=lfs merge=lfs -text
-# Image files - uncompressed
-*.bmp filter=lfs diff=lfs merge=lfs -text
-*.gif filter=lfs diff=lfs merge=lfs -text
-*.png filter=lfs diff=lfs merge=lfs -text
-*.tiff filter=lfs diff=lfs merge=lfs -text
-# Image files - compressed
-*.jpg filter=lfs diff=lfs merge=lfs -text
-*.jpeg filter=lfs diff=lfs merge=lfs -text
-*.webp filter=lfs diff=lfs merge=lfs -text
-# Video files - compressed
-*.mp4 filter=lfs diff=lfs merge=lfs -text
-*.webm filter=lfs diff=lfs merge=lfs -text
+audio/*.tar filter=lfs diff=lfs merge=lfs -text
+figs/audio_span.png filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,3 +1,115 @@
----
-license: cc-by-nc-sa-4.0
----
+# AudioSpan: Spanning the Duration and Depth of Audio Comprehension
+
+[📖 Paper]() | [🧩 AudioSpan Benchmark]()
+
+## Introduction
+
+**AudioSpan** is a benchmark for **long-form audio comprehension**, spanning
+diverse durations and cognitive depths.
+
+<p align="center">
+  <img src="figs/audio_span.png" alt="AudioSpan overview" width="100%">
+</p>
+
+Questions come from two complementary paths:
+
+- **Native QA**: questions drawn from the audio's natural content.
+- **Anchor QA**: questions built around acoustic anchors planted into the
+  audio.
+
+Each path is scored in its own mode:
+
+- **Accuracy**: multiple choice questions on native audio, scored by exact
+  match.
+- **Rubric**: open-ended questions on native audio, graded by rubric-based
+  LLM judges against criteria.
+- **Chain**: multiple-choice question chains on anchor audio; an answer is
+  credited only up to the first error in the chain.
+
+## Quick Start
+
+### 1. Prepare Audio Data
+
+Native recordings and sound events ship as tar archives
+(`audio/audio_native.tar`, `audio/audio_events.tar`). From the release root
+(the directory with `prepare/` and `audio/`), verify them against
+`audio/CHECKSUMS.sha256` and unpack into `audio/`:
+
+```bash
+# accuracy / rubric: native recordings only
+python prepare/unpack_audio.py --buckets native
+# -> audio/native/*.flac
+
+# chain: also rebuild the anchor audio from the native recordings and the
+# exact edit recipes in metadata/media/anchor/anchor_manifest.jsonl
+# (needs only ffmpeg)
+python prepare/unpack_audio.py --buckets native,events
+python prepare/prepare_anchor.py
+# -> audio/anchor/*.flac
+```
+
+(`unpack_audio.py` resolves the release root from its own location; pass
+`--root` if you run it from elsewhere.)
+
+### 2. Prepare Inference Results
+
+The questions live in `metadata/{accuracy,rubric,chain}/{S,M,L}.jsonl`; each
+record carries the question, its `audio_path`, and (for multiple choice) the
+four options. Run your model over each record and write one answer per
+question — only `qa_id` and the model's output; ground truth stays in the
+metadata and is joined in by the scorer:
+
+**accuracy / chain** (multiple choice):
+
+```json
+{"qa_id": "S_EN_001_P", "answer": "D"}
+```
+
+**rubric** (open-ended):
+
+```json
+{"qa_id": "S_EN_001_P", "answer": "The narrator first says HDR at about 06:04 ..."}
+```
+
+- `answer` — the model's raw output; for multiple choice the scorer
+  extracts the option letter (A/B/C/D) from it.
+- Questions missing from your file count as wrong (or score zero).
+
+### 3. Run Evaluation
+
+```bash
+# accuracy + chain: stdlib-only, no dependencies
+python evaluate/score.py --mode accuracy --input your_accuracy.jsonl
+python evaluate/score.py --mode chain    --input your_chain.jsonl
+
+# rubric: needs an LLM judge (default: gpt-5.4-2026-03-05; API key from the
+# matching provider env var, e.g. OPENAI_API_KEY; or pass --api-base/--api-key)
+pip install openai tenacity
+export OPENAI_API_KEY="your-api-key-here"
+python evaluate/score_rubric.py --input your_rubric.jsonl
+```
+
+Both scorers join your answers against the ground truth in `metadata/` by
+`qa_id` — no reference answers needed in your submission.
+
+## License and Data Use
+
+AudioSpan is released for **non-commercial research and evaluation**. Our
+artifacts (QA items, rubric criteria, anchor manifests, sound events, and
+evaluation scripts) are under CC BY-NC-SA 4.0; copyright of the source
+recordings remains with their original creators. The recordings are
+included only for evaluation, and downloading the dataset constitutes
+agreement not to redistribute the audio or use it in commercial products.
+
+## Citation
+
+If you find AudioSpan useful for your research, please consider citing:
+
+```bibtex
+@inproceedings{audiospan,
+  title     = {AudioSpan: ...},
+  author    = {...},
+  booktitle = {...},
+  year      = {2026}
+}
+```

audio/CHECKSUMS.sha256

@@ -0,0 +1,6 @@
+232966e01ef8ab9882c1ce3db0885d7c4f29f463ef9d6d9b792a6dbb7279fc90  audio_native.part00.tar
+17c532041c146856924b681638af662b98c7cfc5b7ab267f027bd6fd97bb8b5e  audio_native.part01.tar
+f7aa8c9ab268dd88dac731eb68660c41c3dd817278f370156a049985e80f649e  audio_native.part02.tar
+e144548e79a8b17526823f32ff5c664a3c972ec3734355f8b95ec2d66c8f7735  audio_native.part03.tar
+bd927c4445ae2b709a6df7a44b4939e2a003be5690571736f93bd6775bbd727f  audio_native.part04.tar
+5fe435eb3a842cc441459925adef41908c7d06681a0901a6a7c9d85db3d10ee1  audio_events.tar

audio/audio_events.tar

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5fe435eb3a842cc441459925adef41908c7d06681a0901a6a7c9d85db3d10ee1
+size 32071680

audio/audio_native.part00.tar

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:232966e01ef8ab9882c1ce3db0885d7c4f29f463ef9d6d9b792a6dbb7279fc90
+size 4294967296

audio/audio_native.part01.tar

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:17c532041c146856924b681638af662b98c7cfc5b7ab267f027bd6fd97bb8b5e
+size 4294967296

audio/audio_native.part02.tar

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f7aa8c9ab268dd88dac731eb68660c41c3dd817278f370156a049985e80f649e
+size 4294967296

audio/audio_native.part03.tar

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e144548e79a8b17526823f32ff5c664a3c972ec3734355f8b95ec2d66c8f7735
+size 4294967296

audio/audio_native.part04.tar

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bd927c4445ae2b709a6df7a44b4939e2a003be5690571736f93bd6775bbd727f
+size 1272631296

evaluate/judge_criteria.md

@@ -0,0 +1,98 @@
+You are an audio-understanding evaluation expert. For each evaluation criterion
+provided, judge the quality of the model's response independently.
+
+## Evaluation Dimensions
+
+### Dimension Selection Rules
+
+Choose which dimension(s) to evaluate based on the criterion's `importance`
+and its content:
+
+**essential criterion: evaluate exactly one dimension**
+- If the criterion requires a specific time point or time span (localization),
+  evaluate **temporal** only; set semantic to `"none"`.
+- If the criterion requires content, meaning, causality, etc. (semantic),
+  evaluate **semantic** only; set temporal to `"none"`.
+
+**supporting criterion: evaluate both dimensions when applicable**
+- If a `time_range` is provided: evaluate both **semantic** and **temporal**.
+- If no `time_range` is provided: evaluate **semantic** only; set temporal to
+  `"none"`.
+
+### semantic
+
+- **correct** = the response fully captures what the criterion requires; the
+  key information is complete and accurate.
+- **partial** = the response touches on part of the content, but key
+  information is incomplete or contains errors.
+- **wrong** = the response does not address what the criterion requires, or
+  the core content is incorrect.
+- **none** = the criterion is a localization task; semantic is not evaluated.
+
+### temporal
+
+- **correct** = the timestamp given by the model falls within the valid range
+  (±5 seconds tolerance around the target), or the time span given by the
+  model overlaps the reference `time_range`.
+- **wrong** = the model produced a timestamp or span, but it is outside the
+  valid range and does not overlap.
+- **missing** = the model did not produce a timestamp (the model is not
+  required to do so).
+- **none** = the criterion is semantic; temporal is not evaluated.
+
+The model may use different timestamp formats. Normalize before comparing:
+- `MM:SS` (e.g. `12:30`) = 12 minutes 30 seconds.
+- Raw seconds (e.g. `522.640秒`) = 8 min 42 sec = `08:42`.
+- Out-of-range minutes (e.g. `64:00`) = `01:04:00`.
+
+Format differences alone do not affect the judgment.
+
+## Judgment Principles
+
+- Focus on whether the core semantics are correct; different wording that
+  expresses the same meaning is acceptable.
+- Evaluate **semantic** and **temporal** independently: semantic judges only
+  whether the content itself is correct, regardless of whether a timestamp is
+  cited. Timestamp citation is judged under temporal.
+- Each criterion is judged on its own requirements only. Details mentioned in
+  other criteria apply to those criteria alone and do not affect this one.
+- A criterion is satisfied as long as the core content is present and correct.
+- Features listed in a criterion are examples; citing the key feature is
+  sufficient.
+- Keep `reason` and `summary` concise: 1–2 sentences each.
+
+## Input
+
+You will receive:
+1. The question (open-ended QA).
+2. A list of evaluation criteria (each with `text`, `importance`, and
+   optionally `time_range`).
+3. The model's response.
+
+## Output Format
+
+```json
+{
+  "criteria": [
+    {
+      "index": 0,
+      "semantic": "none",
+      "temporal": "correct",
+      "reason": "The model timestamp 14:02 is within ±5s of 14:03."
+    },
+    {
+      "index": 1,
+      "semantic": "correct",
+      "temporal": "none",
+      "reason": "The model correctly identifies the motive as loyalty formed from early allegiance to Sun Yat-sen."
+    },
+    {
+      "index": 2,
+      "semantic": "partial",
+      "temporal": "wrong",
+      "reason": "Semantic: the model mentions the vocal features but incompletely. Temporal: the cited timestamp is outside 00:41-00:45."
+    }
+  ],
+  "summary": "A one-sentence summary of the overall quality of the response."
+}
+```

evaluate/score.py

@@ -0,0 +1,215 @@
+#!/usr/bin/env python3
+"""Score model outputs on the AudioSpan release.
+
+Two modes (both stdlib-only, no external dependencies):
+  accuracy — multiple choice on native audio, per-layer breakdown.
+  chain    — first-error truncation over P->U->R chains on anchor audio.
+
+For rubric scoring (which requires a judge model), use score_rubric.py.
+
+The answer file carries only what the model produced, one record per
+question: {"qa_id": ..., "answer": "..."}. For multiple choice the scorer
+extracts the option letter from the answer text. Correct answers and
+question profiles are joined in from metadata/<mode>/{S,M,L}.jsonl;
+questions with no answer count as wrong.
+
+Usage:
+    python score.py --mode accuracy --input results/<model>/accuracy.jsonl
+    python score.py --mode chain    --input results/<model>/chain.jsonl
+"""
+
+import argparse
+import json
+import logging
+import re
+import sys
+from collections import defaultdict
+from pathlib import Path
+
+logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")
+logger = logging.getLogger(__name__)
+
+RELEASE_ROOT = Path(__file__).resolve().parent.parent
+TIERS = ("S", "M", "L")
+LAYER_ORDER = ["perception", "understanding", "reasoning"]
+LAYER_BY_CODE = {"P": "perception", "U": "understanding", "R": "reasoning"}
+
+
+def load_questions(mode: str, data_root: Path) -> list[dict]:
+    questions = []
+    for tier in TIERS:
+        path = data_root / "metadata" / mode / f"{tier}.jsonl"
+        if not path.is_file():
+            sys.exit(f"ERROR: metadata not found: {path}")
+        with open(path, encoding="utf-8") as fh:
+            questions.extend(json.loads(line) for line in fh if line.strip())
+    return questions
+
+
+def extract_option(answer) -> str | None:
+    """Normalize a model answer to an option letter (A-D), or None."""
+    if answer is None:
+        return None
+    if not isinstance(answer, str):
+        answer = str(answer)
+    text = answer.strip()
+    if re.fullmatch(r"[A-Da-d]", text):
+        return text.upper()
+    m = re.search(r"\b(?:answer|option|choice)\s*(?:is|:)?\s*[\(（]?([A-Da-d])[\)）]?\b",
+                  text, re.IGNORECASE)
+    if m:
+        return m.group(1).upper()
+    m = re.search(r"[\(（]([A-Da-d])[\)）]", text)
+    if m:
+        return m.group(1).upper()
+    m = re.fullmatch(r"([A-Da-d])[\.\)、:：].*", text, re.DOTALL)
+    if m:
+        return m.group(1).upper()
+    return None
+
+
+def load_answers(path: str) -> dict[str, str]:
+    """Map qa_id -> raw answer; later duplicates win."""
+    preds: dict[str, str] = {}
+    with open(path, encoding="utf-8", errors="replace") as fh:
+        for lineno, line in enumerate(fh, 1):
+            line = line.strip()
+            if not line:
+                continue
+            try:
+                rec = json.loads(line)
+            except json.JSONDecodeError as e:
+                logger.warning("Skipping bad line %d: %s", lineno, e)
+                continue
+            qa_id = rec.get("qa_id")
+            if not qa_id:
+                logger.warning("Skipping line %d: missing qa_id", lineno)
+                continue
+            preds[qa_id] = rec.get("answer")
+    return preds
+
+
+def score_accuracy(questions: list[dict], preds: dict[str, str]) -> dict:
+    scored = []
+    layer_stats: dict[str, dict[str, int]] = defaultdict(lambda: {"correct": 0, "total": 0})
+
+    for q in questions:
+        predicted = extract_option(preds.get(q["qa_id"]))
+        is_correct = predicted is not None and predicted == q["correct_option"]
+        layer = (q.get("question_profile") or {}).get("level", "unknown")
+        layer_stats[layer]["total"] += 1
+        if is_correct:
+            layer_stats[layer]["correct"] += 1
+        scored.append({"qa_id": q["qa_id"], "predicted": predicted, "correct": is_correct})
+
+    total = len(scored)
+    correct = sum(1 for s in scored if s["correct"])
+    per_layer = {
+        layer: {
+            "accuracy": round(s["correct"] / s["total"] * 100, 2) if s["total"] else 0,
+            "correct": s["correct"], "total": s["total"],
+        }
+        for layer, s in sorted(layer_stats.items())
+    }
+    return {
+        "mode": "accuracy", "total": total, "correct": correct,
+        "accuracy": round(correct / total * 100, 2) if total else 0,
+        "per_layer": per_layer, "scored_records": scored,
+    }
+
+
+def score_chain(questions: list[dict], preds: dict[str, str]) -> dict:
+    layer_correct: dict[str, int] = defaultdict(int)
+    layer_total: dict[str, int] = defaultdict(int)
+    chains: dict[str, dict[str, bool | None]] = defaultdict(lambda: {l: None for l in LAYER_ORDER})
+
+    for q in questions:
+        chain_key, layer_code = q["qa_id"].rsplit("_", 1)
+        layer = LAYER_BY_CODE.get(layer_code)
+        if layer not in LAYER_ORDER:
+            continue
+        predicted = extract_option(preds.get(q["qa_id"]))
+        is_correct = predicted is not None and predicted == q["correct_option"]
+        chains[chain_key][layer] = is_correct
+        layer_total[layer] += 1
+        if is_correct:
+            layer_correct[layer] += 1
+
+    complete = {cid: layers for cid, layers in chains.items()
+                if all(v is not None for v in layers.values())}
+    k = len(LAYER_ORDER)
+
+    n_dist = defaultdict(int)
+    scored = []
+    group_scores = []
+    for cid, layers in complete.items():
+        n = 0
+        for layer in LAYER_ORDER:
+            if layers[layer]:
+                n += 1
+            else:
+                break
+        n_dist[n] += 1
+        group_scores.append(n / k)
+        scored.append({
+            "chain_id": cid,
+            "per_layer": {l: bool(layers[l]) for l in LAYER_ORDER},
+            "n_correct": n,
+            "correct": n == k,
+            "chain_score": round(n / k * 100, 2),
+        })
+
+    chain_score = sum(group_scores) / len(group_scores) * 100 if group_scores else 0
+    per_layer = {
+        layer: {
+            "accuracy": round(layer_correct[layer] / layer_total[layer] * 100, 2) if layer_total[layer] else 0,
+            "correct": layer_correct[layer], "total": layer_total[layer],
+        }
+        for layer in LAYER_ORDER
+    }
+    return {
+        "mode": "chain", "total_chains": len(complete),
+        "chain_score": round(chain_score, 2),
+        "per_layer": per_layer,
+        "n_distribution": {str(n): cnt for n, cnt in sorted(n_dist.items())},
+        "scored_records": scored,
+    }
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Score AudioSpan model outputs (accuracy/chain)")
+    parser.add_argument("--input", required=True,
+                        help="Prediction JSONL: {\"qa_id\": ..., \"answer\": \"...\"} per line")
+    parser.add_argument("--mode", required=True, choices=["accuracy", "chain"])
+    parser.add_argument("--data-root", type=Path, default=RELEASE_ROOT,
+                        help="release root holding metadata/ (default: parent of evaluate/)")
+    parser.add_argument("--output", help="Scored output path (default: <input>_scored.jsonl)")
+    args = parser.parse_args()
+
+    preds = load_answers(args.input)
+    if not preds:
+        print(f"ERROR: no valid answers in {args.input}", file=sys.stderr)
+        sys.exit(1)
+
+    questions = load_questions(args.mode, args.data_root.resolve())
+    known = {q["qa_id"] for q in questions}
+    unknown = sorted(set(preds) - known)
+    if unknown:
+        logger.warning("Ignoring %d unknown qa_id(s), e.g. %s", len(unknown), unknown[0])
+    covered = sum(1 for q in questions if q["qa_id"] in preds)
+    logger.info("Answers cover %d/%d questions (missing count as wrong)", covered, len(questions))
+
+    summary = score_accuracy(questions, preds) if args.mode == "accuracy" else score_chain(questions, preds)
+
+    out_path = args.output or args.input.replace(".jsonl", "_scored.jsonl")
+    with open(out_path, "w", encoding="utf-8") as fh:
+        for s in summary.get("scored_records", []):
+            fh.write(json.dumps(s, ensure_ascii=False) + "\n")
+    logger.info("Scored records: %s", out_path)
+
+    print(json.dumps({k: v for k, v in summary.items() if k != "scored_records"},
+                     indent=2, ensure_ascii=False))
+
+
+if __name__ == "__main__":
+    main()

evaluate/score_rubric.py

@@ -0,0 +1,350 @@
+#!/usr/bin/env python3
+"""Rubric scoring for the AudioSpan release.
+
+Calls a judge model (via the OpenAI chat-completions API) to score each
+criterion on semantic + temporal dimensions, then aggregates with
+importance weights. Depends only on `openai` and `tenacity`.
+
+The answer file carries only what the model produced, one record per
+question: {"qa_id": ..., "answer": "..."}. Questions and criteria are
+joined in from metadata/rubric/{S,M,L}.jsonl; questions with no answer
+score zero.
+
+Usage:
+    python score_rubric.py --input results/<model>/rubric.jsonl \
+                           --judges gpt-5.4-2026-03-05 [--rounds 1]
+"""
+
+import argparse
+import json
+import logging
+import os
+import re
+import sys
+from pathlib import Path
+
+logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")
+logger = logging.getLogger(__name__)
+
+IMPORTANCE_WEIGHT = {"essential": 1.0, "supporting": 0.5}
+VALID_SEMANTIC = {"correct", "partial", "wrong", "none"}
+VALID_TEMPORAL = {"correct", "wrong", "missing", "none"}
+
+SCRIPT_DIR = Path(__file__).resolve().parent
+DEFAULT_JUDGE_PROMPT = SCRIPT_DIR / "judge_criteria.md"
+DEFAULT_JUDGES = ["gpt-5.4-2026-03-05"]
+DEFAULT_ROUNDS = 1
+
+# (prefix, base_url, api_key_env_var). Order matters: first match wins.
+DEFAULT_API_BASEES: list[tuple[str, str, str]] = [
+    ("qwen",    "https://dashscope.aliyuncs.com/compatible-mode/v1",        "DASHSCOPE_API_KEY"),
+    ("gpt",     "https://api.openai.com/v1",                                "OPENAI_API_KEY"),
+    ("o1",      "https://api.openai.com/v1",                                "OPENAI_API_KEY"),
+    ("o3",      "https://api.openai.com/v1",                                "OPENAI_API_KEY"),
+    ("o4",      "https://api.openai.com/v1",                                "OPENAI_API_KEY"),
+    ("gemini",  "https://generativelanguage.googleapis.com/v1beta/openai/", "GEMINI_API_KEY"),
+    ("doubao",  "https://ark.cn-beijing.volces.com/api/v3",                 "ARK_API_KEY"),
+    ("seed",    "https://ark.cn-beijing.volces.com/api/v3",                 "ARK_API_KEY"),
+    ("deepseek","https://api.deepseek.com/v1",                              "DEEPSEEK_API_KEY"),
+]
+
+
+def _resolve_default_api_base(model: str) -> tuple[str, str]:
+    m = model.lower()
+    for prefix, base, env in DEFAULT_API_BASEES:
+        if m == prefix or m.startswith(prefix):
+            nxt = m[len(prefix):len(prefix) + 1]
+            if nxt == "" or not nxt.isalpha():
+                return base, env
+    return "https://api.openai.com/v1", "OPENAI_API_KEY"
+
+
+RELEASE_ROOT = Path(__file__).resolve().parent.parent
+TIERS = ("S", "M", "L")
+
+
+def load_records(input_path: str, data_root: Path) -> list[dict]:
+    """Join answer records with rubric metadata by qa_id."""
+    preds: dict[str, str] = {}
+    with open(input_path, encoding="utf-8", errors="replace") as fh:
+        for lineno, line in enumerate(fh, 1):
+            line = line.strip()
+            if not line:
+                continue
+            try:
+                rec = json.loads(line)
+            except json.JSONDecodeError as e:
+                logger.warning("Skipping bad line %d: %s", lineno, e)
+                continue
+            if rec.get("qa_id"):
+                preds[rec["qa_id"]] = rec.get("answer")
+    if not preds:
+        sys.exit(f"ERROR: no valid answers in {input_path}")
+
+    records = []
+    for tier in TIERS:
+        path = data_root / "metadata" / "rubric" / f"{tier}.jsonl"
+        if not path.is_file():
+            sys.exit(f"ERROR: metadata not found: {path}")
+        with open(path, encoding="utf-8") as fh:
+            for line in fh:
+                if not line.strip():
+                    continue
+                q = json.loads(line)
+                q["model_response"] = preds.get(q["qa_id"])
+                records.append(q)
+
+    unknown = sorted(set(preds) - {r["qa_id"] for r in records})
+    if unknown:
+        logger.warning("Ignoring %d unknown qa_id(s), e.g. %s", len(unknown), unknown[0])
+    covered = sum(1 for r in records if r["model_response"] is not None)
+    logger.info("Answers cover %d/%d questions (missing score zero)", covered, len(records))
+    return records
+
+
+def format_criteria(criteria: list[dict]) -> str:
+    lines = []
+    for i, c in enumerate(criteria):
+        tr = c.get("time_range")
+        tr_str = f" [{tr[0]}-{tr[1]}]" if tr and len(tr) == 2 else ""
+        lines.append(f"{i+1}. [{c.get('importance', 'essential')}]{tr_str} {c['text']}")
+    return "\n".join(lines)
+
+
+_SEM_SCORE = {"correct": 1.0, "partial": 0.5, "wrong": 0.0}
+
+
+def _criterion_score(semantic: str, temporal: str, has_time_range: bool) -> float:
+    sem = _SEM_SCORE.get(semantic, 0.0)
+    if has_time_range:
+        if semantic == "wrong":
+            return 0.0
+        if temporal in ("none", "missing"):
+            return sem
+        return (sem + (1.0 if temporal == "correct" else 0.0)) / 2
+    if temporal in ("correct", "wrong"):
+        return 1.0 if temporal == "correct" else 0.0
+    return sem
+
+
+def _rubric_score(judged: list[dict], ref_criteria: list[dict]) -> float:
+    judged_by_idx = {jc.get("index", i): jc for i, jc in enumerate(judged)}
+    weighted_sum, weight_total = 0.0, 0.0
+    for ref_idx, ref in enumerate(ref_criteria):
+        jc = judged_by_idx.get(ref_idx)
+        if not jc:
+            continue
+        has_tr = ref.get("importance", "essential") != "essential" and ref.get("time_range") is not None
+        w = IMPORTANCE_WEIGHT.get(ref.get("importance", "essential"), 1.0)
+        weighted_sum += w * _criterion_score(jc.get("semantic", "wrong"), jc.get("temporal", "none"), has_tr)
+        weight_total += w
+    return round(weighted_sum / weight_total if weight_total else 0.0, 4)
+
+
+def _trimmed_mean(scores: list[float]) -> float:
+    s = sorted(scores)[1:-1] if len(scores) >= 3 else list(scores)
+    return sum(s) / len(s) if s else 0.0
+
+
+def _extract_json(text: str) -> dict | None:
+    stripped = text.strip()
+    fence = re.search(r"```(?:json)?\s*\n(.*?)\n\s*```", stripped, re.DOTALL)
+    if fence:
+        stripped = fence.group(1).strip()
+    try:
+        return json.loads(stripped)
+    except json.JSONDecodeError:
+        first, last = stripped.find("{"), stripped.rfind("}")
+        if first != -1 and last > first:
+            try:
+                return json.loads(stripped[first:last + 1])
+            except json.JSONDecodeError:
+                return None
+    return None
+
+
+def _load_completed(evals_path: str) -> set[tuple[str, str, int]]:
+    done: set[tuple[str, str, int]] = set()
+    if not os.path.isfile(evals_path):
+        return done
+    with open(evals_path, encoding="utf-8", errors="replace") as fh:
+        for line in fh:
+            line = line.strip()
+            if not line:
+                continue
+            try:
+                ev = json.loads(line)
+                done.add((ev.get("qa_id"), ev["judge"], ev["round"]))
+            except (json.JSONDecodeError, KeyError):
+                continue
+    return done
+
+
+def run_rubric(records: list[dict], judges: list[str], rounds: int,
+               evals_path: str, judge_prompt_path: str,
+               api_base: str, api_key: str) -> dict:
+    from openai import OpenAI
+    from tenacity import retry, stop_after_attempt, wait_exponential_jitter
+
+    system_prompt = Path(judge_prompt_path).read_text(encoding="utf-8")
+    client = OpenAI(api_key=api_key, base_url=api_base)
+
+    done = _load_completed(evals_path)
+    pending = [
+        (rec, judge, r)
+        for rec in records
+        if rec.get("criteria")
+        for judge in judges
+        for r in range(rounds)
+        if (rec["qa_id"], judge, r) not in done
+    ]
+    logger.info("Rubric: %d pending / %d total evals", len(pending),
+                len(records) * len(judges) * rounds)
+
+    write_mode = "a" if done else "w"
+    fh = open(evals_path, write_mode, encoding="utf-8")
+    completed = 0
+
+    @retry(wait=wait_exponential_jitter(initial=3, max=15, exp_base=2, jitter=2),
+           stop=stop_after_attempt(3))
+    def _call_judge(judge: str, user_msg: str) -> str:
+        resp = client.chat.completions.create(
+            model=judge,
+            messages=[{"role": "system", "content": system_prompt},
+                      {"role": "user", "content": user_msg}],
+            max_tokens=3000, temperature=0.0,
+            response_format={"type": "json_object"},
+        )
+        return resp.choices[0].message.content or ""
+
+    try:
+        for rec, judge, round_idx in pending:
+            user_msg = (
+                f"## Question\n\n{rec['question']}\n\n"
+                f"## Evaluation Criteria\n\n{format_criteria(rec['criteria'])}\n\n"
+                f"## Model Response\n\n{rec.get('model_response') or ''}"
+            )
+            judged = None
+            for _ in range(3):
+                try:
+                    raw = _call_judge(judge, user_msg)
+                    result = _extract_json(raw) or {}
+                    judged = result.get("criteria", [])
+                    for j in judged:
+                        if j.get("temporal") == "partial":
+                            j["temporal"] = "correct"
+                    if len(judged) != len(rec["criteria"]):
+                        judged = None
+                        continue
+                    if any(j.get("semantic") not in VALID_SEMANTIC
+                           or j.get("temporal") not in VALID_TEMPORAL
+                           for j in judged):
+                        judged = None
+                        continue
+                    break
+                except Exception as e:
+                    logger.warning("Judge %s id=%s: %s", judge, rec["qa_id"], str(e)[:120])
+                    judged = None
+            if not judged:
+                logger.warning("Judge %s id=%s: all attempts failed", judge, rec["qa_id"])
+                continue
+            score = _rubric_score(judged, rec["criteria"])
+            ev = {
+                "qa_id": rec["qa_id"], "judge": judge, "round": round_idx, "score": score,
+                "criteria": [
+                    {"index": j.get("index", j_idx),
+                     "importance": rec["criteria"][j_idx].get("importance", "essential"),
+                     "semantic": j.get("semantic"), "temporal": j.get("temporal"),
+                     "score": _criterion_score(
+                         j.get("semantic"), j.get("temporal"),
+                         rec["criteria"][j_idx].get("importance", "essential") != "essential"
+                         and rec["criteria"][j_idx].get("time_range") is not None,
+                     )}
+                    for j_idx, j in enumerate(judged)
+                ],
+            }
+            fh.write(json.dumps(ev, ensure_ascii=False) + "\n")
+            fh.flush()
+            completed += 1
+            if completed % 50 == 0:
+                logger.info("Rubric progress: %d/%d", completed, len(pending))
+    finally:
+        fh.close()
+
+    return _aggregate(evals_path, records, judges)
+
+
+def _aggregate(evals_path: str, records: list[dict], judges: list[str]) -> dict:
+    evals_by_id: dict[str, list[dict]] = {}
+    with open(evals_path, encoding="utf-8", errors="replace") as fh:
+        for line in fh:
+            line = line.strip()
+            if not line:
+                continue
+            try:
+                ev = json.loads(line)
+            except json.JSONDecodeError:
+                continue
+            evals_by_id.setdefault(ev.get("qa_id"), []).append(ev)
+
+    scored = []
+    for rec in records:
+        evals = [e for e in evals_by_id.get(rec["qa_id"], [])
+                 if e.get("judge") == judges[0]]
+        score = round(_trimmed_mean([e["score"] for e in evals]) * 100, 2) if evals else 0
+        scored.append({"qa_id": rec["qa_id"], "score": score})
+
+    total = len(scored)
+    mean = sum(s["score"] for s in scored) / total if total else 0
+    return {"mode": "rubric", "total": total,
+            "avg_score": round(mean, 2), "scored_records": scored}
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Rubric-score AudioSpan model outputs")
+    parser.add_argument("--input", required=True,
+                        help="Prediction JSONL: {\"qa_id\": ..., \"answer\": \"...\"} per line")
+    parser.add_argument("--output", help="Aggregated scored JSONL (default: <input>_scored.jsonl)")
+    parser.add_argument("--evals", help="Per-eval JSONL (default: <input>_evals.jsonl)")
+    parser.add_argument("--data-root", type=Path, default=RELEASE_ROOT,
+                        help="release root holding metadata/ (default: parent of evaluate/)")
+    parser.add_argument("--judges", help="Comma-separated judge models")
+    parser.add_argument("--rounds", type=int, default=DEFAULT_ROUNDS)
+    parser.add_argument("--judge-prompt", default=str(DEFAULT_JUDGE_PROMPT))
+    parser.add_argument("--api-base",
+                        help="OpenAI-compatible base URL (default: inferred from first judge)")
+    parser.add_argument("--api-key",
+                        help="API key (default: provider env var, see module docstring)")
+    args = parser.parse_args()
+
+    records = load_records(args.input, args.data_root.resolve())
+
+    judges = args.judges.split(",") if args.judges else DEFAULT_JUDGES
+    default_base, default_env = _resolve_default_api_base(judges[0])
+    if not args.api_base:
+        args.api_base = default_base
+        logger.info("Resolved --api-base from judge %r: %s", judges[0], args.api_base)
+    if not args.api_key:
+        args.api_key = os.environ.get(default_env) or os.environ.get("OPENAI_API_KEY")
+    if not args.api_key:
+        parser.error(f"--api-key or {default_env} required for judge {judges[0]!r}")
+
+    evals_path = args.evals or args.input.replace(".jsonl", "_evals.jsonl")
+    summary = run_rubric(
+        records, judges, args.rounds, evals_path,
+        judge_prompt_path=args.judge_prompt,
+        api_base=args.api_base, api_key=args.api_key,
+    )
+
+    out_path = args.output or args.input.replace(".jsonl", "_scored.jsonl")
+    with open(out_path, "w", encoding="utf-8") as fh:
+        for s in summary.get("scored_records", []):
+            fh.write(json.dumps(s, ensure_ascii=False) + "\n")
+    logger.info("Scored records: %s", out_path)
+
+    print(json.dumps({k: v for k, v in summary.items() if k != "scored_records"},
+                     indent=2, ensure_ascii=False))
+
+
+if __name__ == "__main__":
+    main()

metadata/media/anchor/L.jsonl

@@ -0,0 +1,120 @@
+{"media_id": "L_EN_001_D", "operation": "deletion", "audio_path": "audio/anchor/L_EN_001_D.flac", "duration_sec": 4358.88475}
+{"media_id": "L_EN_002_D", "operation": "deletion", "audio_path": "audio/anchor/L_EN_002_D.flac", "duration_sec": 4945.711063}
+{"media_id": "L_EN_003_M", "operation": "modification", "audio_path": "audio/anchor/L_EN_003_M.flac", "duration_sec": 3645.662688}
+{"media_id": "L_EN_004_M", "operation": "modification", "audio_path": "audio/anchor/L_EN_004_M.flac", "duration_sec": 5275.3645}
+{"media_id": "L_EN_005_M", "operation": "modification", "audio_path": "audio/anchor/L_EN_005_M.flac", "duration_sec": 5220.844313}
+{"media_id": "L_EN_006_A", "operation": "addition", "audio_path": "audio/anchor/L_EN_006_A.flac", "duration_sec": 5714.605}
+{"media_id": "L_EN_007_D", "operation": "deletion", "audio_path": "audio/anchor/L_EN_007_D.flac", "duration_sec": 4755.81825}
+{"media_id": "L_EN_008_M", "operation": "modification", "audio_path": "audio/anchor/L_EN_008_M.flac", "duration_sec": 7792.753188}
+{"media_id": "L_EN_009_A", "operation": "addition", "audio_path": "audio/anchor/L_EN_009_A.flac", "duration_sec": 3946.1385}
+{"media_id": "L_EN_010_M", "operation": "modification", "audio_path": "audio/anchor/L_EN_010_M.flac", "duration_sec": 4087.73375}
+{"media_id": "L_EN_011_D", "operation": "deletion", "audio_path": "audio/anchor/L_EN_011_D.flac", "duration_sec": 8315.147063}
+{"media_id": "L_EN_012_A", "operation": "addition", "audio_path": "audio/anchor/L_EN_012_A.flac", "duration_sec": 3879.24175}
+{"media_id": "L_EN_013_D", "operation": "deletion", "audio_path": "audio/anchor/L_EN_013_D.flac", "duration_sec": 6221.09025}
+{"media_id": "L_EN_014_D", "operation": "deletion", "audio_path": "audio/anchor/L_EN_014_D.flac", "duration_sec": 5581.682375}
+{"media_id": "L_EN_015_A", "operation": "addition", "audio_path": "audio/anchor/L_EN_015_A.flac", "duration_sec": 3641.353375}
+{"media_id": "L_EN_016_M", "operation": "modification", "audio_path": "audio/anchor/L_EN_016_M.flac", "duration_sec": 4169.409938}
+{"media_id": "L_EN_017_A", "operation": "addition", "audio_path": "audio/anchor/L_EN_017_A.flac", "duration_sec": 4284.824688}
+{"media_id": "L_EN_018_A", "operation": "addition", "audio_path": "audio/anchor/L_EN_018_A.flac", "duration_sec": 4372.363938}
+{"media_id": "L_EN_019_M", "operation": "modification", "audio_path": "audio/anchor/L_EN_019_M.flac", "duration_sec": 4021.510438}
+{"media_id": "L_EN_020_D", "operation": "deletion", "audio_path": "audio/anchor/L_EN_020_D.flac", "duration_sec": 6449.899688}
+{"media_id": "L_EN_021_D", "operation": "deletion", "audio_path": "audio/anchor/L_EN_021_D.flac", "duration_sec": 7624.701688}
+{"media_id": "L_EN_022_A", "operation": "addition", "audio_path": "audio/anchor/L_EN_022_A.flac", "duration_sec": 5067.302375}
+{"media_id": "L_EN_023_D", "operation": "deletion", "audio_path": "audio/anchor/L_EN_023_D.flac", "duration_sec": 4613.12}
+{"media_id": "L_EN_024_M", "operation": "modification", "audio_path": "audio/anchor/L_EN_024_M.flac", "duration_sec": 5009.769813}
+{"media_id": "L_EN_025_D", "operation": "deletion", "audio_path": "audio/anchor/L_EN_025_D.flac", "duration_sec": 4304.042688}
+{"media_id": "L_EN_026_A", "operation": "addition", "audio_path": "audio/anchor/L_EN_026_A.flac", "duration_sec": 3689.975938}
+{"media_id": "L_EN_027_M", "operation": "modification", "audio_path": "audio/anchor/L_EN_027_M.flac", "duration_sec": 5418.132625}
+{"media_id": "L_EN_028_M", "operation": "modification", "audio_path": "audio/anchor/L_EN_028_M.flac", "duration_sec": 3640.470938}
+{"media_id": "L_EN_029_A", "operation": "addition", "audio_path": "audio/anchor/L_EN_029_A.flac", "duration_sec": 6958.521188}
+{"media_id": "L_EN_030_A", "operation": "addition", "audio_path": "audio/anchor/L_EN_030_A.flac", "duration_sec": 5032.228625}
+{"media_id": "L_EN_031_D", "operation": "deletion", "audio_path": "audio/anchor/L_EN_031_D.flac", "duration_sec": 4311.388313}
+{"media_id": "L_EN_032_M", "operation": "modification", "audio_path": "audio/anchor/L_EN_032_M.flac", "duration_sec": 8013.134625}
+{"media_id": "L_EN_033_D", "operation": "deletion", "audio_path": "audio/anchor/L_EN_033_D.flac", "duration_sec": 4695.875938}
+{"media_id": "L_EN_034_M", "operation": "modification", "audio_path": "audio/anchor/L_EN_034_M.flac", "duration_sec": 4481.522}
+{"media_id": "L_EN_035_D", "operation": "deletion", "audio_path": "audio/anchor/L_EN_035_D.flac", "duration_sec": 7024.616813}
+{"media_id": "L_EN_036_M", "operation": "modification", "audio_path": "audio/anchor/L_EN_036_M.flac", "duration_sec": 5224.524688}
+{"media_id": "L_EN_037_A", "operation": "addition", "audio_path": "audio/anchor/L_EN_037_A.flac", "duration_sec": 3759.381375}
+{"media_id": "L_EN_038_A", "operation": "addition", "audio_path": "audio/anchor/L_EN_038_A.flac", "duration_sec": 6372.99525}
+{"media_id": "L_EN_039_A", "operation": "addition", "audio_path": "audio/anchor/L_EN_039_A.flac", "duration_sec": 5303.484125}
+{"media_id": "L_EN_040_D", "operation": "deletion", "audio_path": "audio/anchor/L_EN_040_D.flac", "duration_sec": 4635.376375}
+{"media_id": "L_EN_041_M", "operation": "modification", "audio_path": "audio/anchor/L_EN_041_M.flac", "duration_sec": 4919.825625}
+{"media_id": "L_EN_042_A", "operation": "addition", "audio_path": "audio/anchor/L_EN_042_A.flac", "duration_sec": 5462.912}
+{"media_id": "L_EN_043_A", "operation": "addition", "audio_path": "audio/anchor/L_EN_043_A.flac", "duration_sec": 9514.283563}
+{"media_id": "L_EN_044_D", "operation": "deletion", "audio_path": "audio/anchor/L_EN_044_D.flac", "duration_sec": 4337.359875}
+{"media_id": "L_EN_045_M", "operation": "modification", "audio_path": "audio/anchor/L_EN_045_M.flac", "duration_sec": 8953.335875}
+{"media_id": "L_EN_046_M", "operation": "modification", "audio_path": "audio/anchor/L_EN_046_M.flac", "duration_sec": 4351.605313}
+{"media_id": "L_EN_047_A", "operation": "addition", "audio_path": "audio/anchor/L_EN_047_A.flac", "duration_sec": 3906.333375}
+{"media_id": "L_EN_048_A", "operation": "addition", "audio_path": "audio/anchor/L_EN_048_A.flac", "duration_sec": 6574.08}
+{"media_id": "L_EN_049_D", "operation": "deletion", "audio_path": "audio/anchor/L_EN_049_D.flac", "duration_sec": 7109.079375}
+{"media_id": "L_EN_050_A", "operation": "addition", "audio_path": "audio/anchor/L_EN_050_A.flac", "duration_sec": 7507.84}
+{"media_id": "L_EN_051_D", "operation": "deletion", "audio_path": "audio/anchor/L_EN_051_D.flac", "duration_sec": 4138.875688}
+{"media_id": "L_EN_052_M", "operation": "modification", "audio_path": "audio/anchor/L_EN_052_M.flac", "duration_sec": 5943.04}
+{"media_id": "L_EN_053_A", "operation": "addition", "audio_path": "audio/anchor/L_EN_053_A.flac", "duration_sec": 8356.992}
+{"media_id": "L_EN_054_M", "operation": "modification", "audio_path": "audio/anchor/L_EN_054_M.flac", "duration_sec": 4845.518188}
+{"media_id": "L_EN_055_D", "operation": "deletion", "audio_path": "audio/anchor/L_EN_055_D.flac", "duration_sec": 5249.103}
+{"media_id": "L_EN_056_M", "operation": "modification", "audio_path": "audio/anchor/L_EN_056_M.flac", "duration_sec": 3643.08725}
+{"media_id": "L_EN_057_A", "operation": "addition", "audio_path": "audio/anchor/L_EN_057_A.flac", "duration_sec": 3951.223625}
+{"media_id": "L_EN_058_M", "operation": "modification", "audio_path": "audio/anchor/L_EN_058_M.flac", "duration_sec": 8480.066813}
+{"media_id": "L_EN_059_D", "operation": "deletion", "audio_path": "audio/anchor/L_EN_059_D.flac", "duration_sec": 3648.490688}
+{"media_id": "L_EN_060_D", "operation": "deletion", "audio_path": "audio/anchor/L_EN_060_D.flac", "duration_sec": 7897.234313}
+{"media_id": "L_ZH_001_A", "operation": "addition", "audio_path": "audio/anchor/L_ZH_001_A.flac", "duration_sec": 9813.147625}
+{"media_id": "L_ZH_002_D", "operation": "deletion", "audio_path": "audio/anchor/L_ZH_002_D.flac", "duration_sec": 8349.884125}
+{"media_id": "L_ZH_003_A", "operation": "addition", "audio_path": "audio/anchor/L_ZH_003_A.flac", "duration_sec": 3888.018875}
+{"media_id": "L_ZH_004_M", "operation": "modification", "audio_path": "audio/anchor/L_ZH_004_M.flac", "duration_sec": 3642.584}
+{"media_id": "L_ZH_005_D", "operation": "deletion", "audio_path": "audio/anchor/L_ZH_005_D.flac", "duration_sec": 4143.624188}
+{"media_id": "L_ZH_006_A", "operation": "addition", "audio_path": "audio/anchor/L_ZH_006_A.flac", "duration_sec": 8349.013375}
+{"media_id": "L_ZH_007_M", "operation": "modification", "audio_path": "audio/anchor/L_ZH_007_M.flac", "duration_sec": 4050.686313}
+{"media_id": "L_ZH_008_D", "operation": "deletion", "audio_path": "audio/anchor/L_ZH_008_D.flac", "duration_sec": 4408.169125}
+{"media_id": "L_ZH_009_A", "operation": "addition", "audio_path": "audio/anchor/L_ZH_009_A.flac", "duration_sec": 4401.563}
+{"media_id": "L_ZH_010_M", "operation": "modification", "audio_path": "audio/anchor/L_ZH_010_M.flac", "duration_sec": 3699.164375}
+{"media_id": "L_ZH_011_A", "operation": "addition", "audio_path": "audio/anchor/L_ZH_011_A.flac", "duration_sec": 4511.126375}
+{"media_id": "L_ZH_012_A", "operation": "addition", "audio_path": "audio/anchor/L_ZH_012_A.flac", "duration_sec": 5157.610688}
+{"media_id": "L_ZH_013_M", "operation": "modification", "audio_path": "audio/anchor/L_ZH_013_M.flac", "duration_sec": 8307.711063}
+{"media_id": "L_ZH_014_D", "operation": "deletion", "audio_path": "audio/anchor/L_ZH_014_D.flac", "duration_sec": 7498.094938}
+{"media_id": "L_ZH_015_A", "operation": "addition", "audio_path": "audio/anchor/L_ZH_015_A.flac", "duration_sec": 4377.72775}
+{"media_id": "L_ZH_016_M", "operation": "modification", "audio_path": "audio/anchor/L_ZH_016_M.flac", "duration_sec": 8537.474875}
+{"media_id": "L_ZH_017_A", "operation": "addition", "audio_path": "audio/anchor/L_ZH_017_A.flac", "duration_sec": 7279.5255}
+{"media_id": "L_ZH_018_A", "operation": "addition", "audio_path": "audio/anchor/L_ZH_018_A.flac", "duration_sec": 6272.49925}
+{"media_id": "L_ZH_019_D", "operation": "deletion", "audio_path": "audio/anchor/L_ZH_019_D.flac", "duration_sec": 4458.208125}
+{"media_id": "L_ZH_020_D", "operation": "deletion", "audio_path": "audio/anchor/L_ZH_020_D.flac", "duration_sec": 5586.001313}
+{"media_id": "L_ZH_021_M", "operation": "modification", "audio_path": "audio/anchor/L_ZH_021_M.flac", "duration_sec": 5064.063188}
+{"media_id": "L_ZH_022_M", "operation": "modification", "audio_path": "audio/anchor/L_ZH_022_M.flac", "duration_sec": 3885.604}
+{"media_id": "L_ZH_023_A", "operation": "addition", "audio_path": "audio/anchor/L_ZH_023_A.flac", "duration_sec": 3650.153688}
+{"media_id": "L_ZH_024_D", "operation": "deletion", "audio_path": "audio/anchor/L_ZH_024_D.flac", "duration_sec": 5419.920563}
+{"media_id": "L_ZH_025_M", "operation": "modification", "audio_path": "audio/anchor/L_ZH_025_M.flac", "duration_sec": 7500.591063}
+{"media_id": "L_ZH_026_A", "operation": "addition", "audio_path": "audio/anchor/L_ZH_026_A.flac", "duration_sec": 5460.66}
+{"media_id": "L_ZH_027_D", "operation": "deletion", "audio_path": "audio/anchor/L_ZH_027_D.flac", "duration_sec": 5376.213375}
+{"media_id": "L_ZH_028_D", "operation": "deletion", "audio_path": "audio/anchor/L_ZH_028_D.flac", "duration_sec": 4295.7265}
+{"media_id": "L_ZH_029_M", "operation": "modification", "audio_path": "audio/anchor/L_ZH_029_M.flac", "duration_sec": 3804.961313}
+{"media_id": "L_ZH_030_A", "operation": "addition", "audio_path": "audio/anchor/L_ZH_030_A.flac", "duration_sec": 5296.076938}
+{"media_id": "L_ZH_031_D", "operation": "deletion", "audio_path": "audio/anchor/L_ZH_031_D.flac", "duration_sec": 5031.274688}
+{"media_id": "L_ZH_032_D", "operation": "deletion", "audio_path": "audio/anchor/L_ZH_032_D.flac", "duration_sec": 4080.6865}
+{"media_id": "L_ZH_033_M", "operation": "modification", "audio_path": "audio/anchor/L_ZH_033_M.flac", "duration_sec": 4603.634688}
+{"media_id": "L_ZH_034_M", "operation": "modification", "audio_path": "audio/anchor/L_ZH_034_M.flac", "duration_sec": 5007.429688}
+{"media_id": "L_ZH_035_A", "operation": "addition", "audio_path": "audio/anchor/L_ZH_035_A.flac", "duration_sec": 5695.019}
+{"media_id": "L_ZH_036_D", "operation": "deletion", "audio_path": "audio/anchor/L_ZH_036_D.flac", "duration_sec": 7525.033375}
+{"media_id": "L_ZH_037_D", "operation": "deletion", "audio_path": "audio/anchor/L_ZH_037_D.flac", "duration_sec": 5908.689}
+{"media_id": "L_ZH_038_M", "operation": "modification", "audio_path": "audio/anchor/L_ZH_038_M.flac", "duration_sec": 4642.656938}
+{"media_id": "L_ZH_039_D", "operation": "deletion", "audio_path": "audio/anchor/L_ZH_039_D.flac", "duration_sec": 5557.661375}
+{"media_id": "L_ZH_040_M", "operation": "modification", "audio_path": "audio/anchor/L_ZH_040_M.flac", "duration_sec": 4565.506438}
+{"media_id": "L_ZH_041_M", "operation": "modification", "audio_path": "audio/anchor/L_ZH_041_M.flac", "duration_sec": 3894.8235}
+{"media_id": "L_ZH_042_A", "operation": "addition", "audio_path": "audio/anchor/L_ZH_042_A.flac", "duration_sec": 4798.9145}
+{"media_id": "L_ZH_043_A", "operation": "addition", "audio_path": "audio/anchor/L_ZH_043_A.flac", "duration_sec": 4024.389688}
+{"media_id": "L_ZH_044_D", "operation": "deletion", "audio_path": "audio/anchor/L_ZH_044_D.flac", "duration_sec": 5494.700438}
+{"media_id": "L_ZH_045_M", "operation": "modification", "audio_path": "audio/anchor/L_ZH_045_M.flac", "duration_sec": 3928.0825}
+{"media_id": "L_ZH_046_D", "operation": "deletion", "audio_path": "audio/anchor/L_ZH_046_D.flac", "duration_sec": 3868.223875}
+{"media_id": "L_ZH_047_A", "operation": "addition", "audio_path": "audio/anchor/L_ZH_047_A.flac", "duration_sec": 8786.953375}
+{"media_id": "L_ZH_048_M", "operation": "modification", "audio_path": "audio/anchor/L_ZH_048_M.flac", "duration_sec": 3742.069875}
+{"media_id": "L_ZH_049_A", "operation": "addition", "audio_path": "audio/anchor/L_ZH_049_A.flac", "duration_sec": 4950.564}
+{"media_id": "L_ZH_050_A", "operation": "addition", "audio_path": "audio/anchor/L_ZH_050_A.flac", "duration_sec": 6136.883125}
+{"media_id": "L_ZH_051_D", "operation": "deletion", "audio_path": "audio/anchor/L_ZH_051_D.flac", "duration_sec": 4917.72}
+{"media_id": "L_ZH_052_M", "operation": "modification", "audio_path": "audio/anchor/L_ZH_052_M.flac", "duration_sec": 5227.766125}
+{"media_id": "L_ZH_053_A", "operation": "addition", "audio_path": "audio/anchor/L_ZH_053_A.flac", "duration_sec": 4890.28}
+{"media_id": "L_ZH_054_D", "operation": "deletion", "audio_path": "audio/anchor/L_ZH_054_D.flac", "duration_sec": 5530.076063}
+{"media_id": "L_ZH_055_M", "operation": "modification", "audio_path": "audio/anchor/L_ZH_055_M.flac", "duration_sec": 4024.668313}
+{"media_id": "L_ZH_056_D", "operation": "deletion", "audio_path": "audio/anchor/L_ZH_056_D.flac", "duration_sec": 5340.345813}
+{"media_id": "L_ZH_057_D", "operation": "deletion", "audio_path": "audio/anchor/L_ZH_057_D.flac", "duration_sec": 3858.146438}
+{"media_id": "L_ZH_058_A", "operation": "addition", "audio_path": "audio/anchor/L_ZH_058_A.flac", "duration_sec": 3862.08}
+{"media_id": "L_ZH_059_M", "operation": "modification", "audio_path": "audio/anchor/L_ZH_059_M.flac", "duration_sec": 5165.673688}
+{"media_id": "L_ZH_060_M", "operation": "modification", "audio_path": "audio/anchor/L_ZH_060_M.flac", "duration_sec": 9597.575813}

metadata/media/anchor/M.jsonl

@@ -0,0 +1,120 @@
+{"media_id": "M_EN_001_M", "operation": "modification", "audio_path": "audio/anchor/M_EN_001_M.flac", "duration_sec": 1867.68475}
+{"media_id": "M_EN_002_M", "operation": "modification", "audio_path": "audio/anchor/M_EN_002_M.flac", "duration_sec": 2381.022938}
+{"media_id": "M_EN_003_D", "operation": "deletion", "audio_path": "audio/anchor/M_EN_003_D.flac", "duration_sec": 1981.35875}
+{"media_id": "M_EN_004_A", "operation": "addition", "audio_path": "audio/anchor/M_EN_004_A.flac", "duration_sec": 3538.272}
+{"media_id": "M_EN_005_D", "operation": "deletion", "audio_path": "audio/anchor/M_EN_005_D.flac", "duration_sec": 3346.090688}
+{"media_id": "M_EN_006_D", "operation": "deletion", "audio_path": "audio/anchor/M_EN_006_D.flac", "duration_sec": 2407.317375}
+{"media_id": "M_EN_007_A", "operation": "addition", "audio_path": "audio/anchor/M_EN_007_A.flac", "duration_sec": 2576.300438}
+{"media_id": "M_EN_008_M", "operation": "modification", "audio_path": "audio/anchor/M_EN_008_M.flac", "duration_sec": 2264.65825}
+{"media_id": "M_EN_009_D", "operation": "deletion", "audio_path": "audio/anchor/M_EN_009_D.flac", "duration_sec": 1823.01025}
+{"media_id": "M_EN_010_A", "operation": "addition", "audio_path": "audio/anchor/M_EN_010_A.flac", "duration_sec": 2192.184313}
+{"media_id": "M_EN_011_M", "operation": "modification", "audio_path": "audio/anchor/M_EN_011_M.flac", "duration_sec": 3122.419563}
+{"media_id": "M_EN_012_M", "operation": "modification", "audio_path": "audio/anchor/M_EN_012_M.flac", "duration_sec": 1861.892125}
+{"media_id": "M_EN_013_A", "operation": "addition", "audio_path": "audio/anchor/M_EN_013_A.flac", "duration_sec": 2446.01325}
+{"media_id": "M_EN_014_D", "operation": "deletion", "audio_path": "audio/anchor/M_EN_014_D.flac", "duration_sec": 3290.012188}
+{"media_id": "M_EN_015_A", "operation": "addition", "audio_path": "audio/anchor/M_EN_015_A.flac", "duration_sec": 2590.615563}
+{"media_id": "M_EN_016_A", "operation": "addition", "audio_path": "audio/anchor/M_EN_016_A.flac", "duration_sec": 2610.689188}
+{"media_id": "M_EN_017_D", "operation": "deletion", "audio_path": "audio/anchor/M_EN_017_D.flac", "duration_sec": 2042.334375}
+{"media_id": "M_EN_018_M", "operation": "modification", "audio_path": "audio/anchor/M_EN_018_M.flac", "duration_sec": 2502.442688}
+{"media_id": "M_EN_019_D", "operation": "deletion", "audio_path": "audio/anchor/M_EN_019_D.flac", "duration_sec": 2349.139625}
+{"media_id": "M_EN_020_A", "operation": "addition", "audio_path": "audio/anchor/M_EN_020_A.flac", "duration_sec": 2483.757313}
+{"media_id": "M_EN_021_M", "operation": "modification", "audio_path": "audio/anchor/M_EN_021_M.flac", "duration_sec": 3573.322625}
+{"media_id": "M_EN_022_A", "operation": "addition", "audio_path": "audio/anchor/M_EN_022_A.flac", "duration_sec": 1830.037375}
+{"media_id": "M_EN_023_A", "operation": "addition", "audio_path": "audio/anchor/M_EN_023_A.flac", "duration_sec": 2458.145688}
+{"media_id": "M_EN_024_D", "operation": "deletion", "audio_path": "audio/anchor/M_EN_024_D.flac", "duration_sec": 2002.517375}
+{"media_id": "M_EN_025_M", "operation": "modification", "audio_path": "audio/anchor/M_EN_025_M.flac", "duration_sec": 2530.46425}
+{"media_id": "M_EN_026_M", "operation": "modification", "audio_path": "audio/anchor/M_EN_026_M.flac", "duration_sec": 2278.411625}
+{"media_id": "M_EN_027_A", "operation": "addition", "audio_path": "audio/anchor/M_EN_027_A.flac", "duration_sec": 1974.218625}
+{"media_id": "M_EN_028_A", "operation": "addition", "audio_path": "audio/anchor/M_EN_028_A.flac", "duration_sec": 1813.525438}
+{"media_id": "M_EN_029_D", "operation": "deletion", "audio_path": "audio/anchor/M_EN_029_D.flac", "duration_sec": 1910.9675}
+{"media_id": "M_EN_030_M", "operation": "modification", "audio_path": "audio/anchor/M_EN_030_M.flac", "duration_sec": 2062.761188}
+{"media_id": "M_EN_031_A", "operation": "addition", "audio_path": "audio/anchor/M_EN_031_A.flac", "duration_sec": 2282.325438}
+{"media_id": "M_EN_032_D", "operation": "deletion", "audio_path": "audio/anchor/M_EN_032_D.flac", "duration_sec": 2041.452}
+{"media_id": "M_EN_033_M", "operation": "modification", "audio_path": "audio/anchor/M_EN_033_M.flac", "duration_sec": 2392.271313}
+{"media_id": "M_EN_034_A", "operation": "addition", "audio_path": "audio/anchor/M_EN_034_A.flac", "duration_sec": 2200.832}
+{"media_id": "M_EN_035_M", "operation": "modification", "audio_path": "audio/anchor/M_EN_035_M.flac", "duration_sec": 1818.58175}
+{"media_id": "M_EN_036_D", "operation": "deletion", "audio_path": "audio/anchor/M_EN_036_D.flac", "duration_sec": 2185.044188}
+{"media_id": "M_EN_037_A", "operation": "addition", "audio_path": "audio/anchor/M_EN_037_A.flac", "duration_sec": 2051.274063}
+{"media_id": "M_EN_038_M", "operation": "modification", "audio_path": "audio/anchor/M_EN_038_M.flac", "duration_sec": 3219.09225}
+{"media_id": "M_EN_039_D", "operation": "deletion", "audio_path": "audio/anchor/M_EN_039_D.flac", "duration_sec": 3274.826313}
+{"media_id": "M_EN_040_A", "operation": "addition", "audio_path": "audio/anchor/M_EN_040_A.flac", "duration_sec": 2842.819063}
+{"media_id": "M_EN_041_D", "operation": "deletion", "audio_path": "audio/anchor/M_EN_041_D.flac", "duration_sec": 2624.029063}
+{"media_id": "M_EN_042_A", "operation": "addition", "audio_path": "audio/anchor/M_EN_042_A.flac", "duration_sec": 2196.096}
+{"media_id": "M_EN_043_M", "operation": "modification", "audio_path": "audio/anchor/M_EN_043_M.flac", "duration_sec": 1960.896}
+{"media_id": "M_EN_044_M", "operation": "modification", "audio_path": "audio/anchor/M_EN_044_M.flac", "duration_sec": 2102.186313}
+{"media_id": "M_EN_045_D", "operation": "deletion", "audio_path": "audio/anchor/M_EN_045_D.flac", "duration_sec": 2319.789625}
+{"media_id": "M_EN_046_A", "operation": "addition", "audio_path": "audio/anchor/M_EN_046_A.flac", "duration_sec": 1881.872875}
+{"media_id": "M_EN_047_D", "operation": "deletion", "audio_path": "audio/anchor/M_EN_047_D.flac", "duration_sec": 2466.504875}
+{"media_id": "M_EN_048_M", "operation": "modification", "audio_path": "audio/anchor/M_EN_048_M.flac", "duration_sec": 1998.801313}
+{"media_id": "M_EN_049_D", "operation": "deletion", "audio_path": "audio/anchor/M_EN_049_D.flac", "duration_sec": 2391.445375}
+{"media_id": "M_EN_050_M", "operation": "modification", "audio_path": "audio/anchor/M_EN_050_M.flac", "duration_sec": 1968.385625}
+{"media_id": "M_EN_051_A", "operation": "addition", "audio_path": "audio/anchor/M_EN_051_A.flac", "duration_sec": 3579.866875}
+{"media_id": "M_EN_052_D", "operation": "deletion", "audio_path": "audio/anchor/M_EN_052_D.flac", "duration_sec": 2155.578063}
+{"media_id": "M_EN_053_D", "operation": "deletion", "audio_path": "audio/anchor/M_EN_053_D.flac", "duration_sec": 3132.058438}
+{"media_id": "M_EN_054_M", "operation": "modification", "audio_path": "audio/anchor/M_EN_054_M.flac", "duration_sec": 2127.856563}
+{"media_id": "M_EN_055_M", "operation": "modification", "audio_path": "audio/anchor/M_EN_055_M.flac", "duration_sec": 2991.194563}
+{"media_id": "M_EN_056_A", "operation": "addition", "audio_path": "audio/anchor/M_EN_056_A.flac", "duration_sec": 2251.178688}
+{"media_id": "M_EN_057_D", "operation": "deletion", "audio_path": "audio/anchor/M_EN_057_D.flac", "duration_sec": 3421.495188}
+{"media_id": "M_EN_058_D", "operation": "deletion", "audio_path": "audio/anchor/M_EN_058_D.flac", "duration_sec": 3396.352}
+{"media_id": "M_EN_059_A", "operation": "addition", "audio_path": "audio/anchor/M_EN_059_A.flac", "duration_sec": 3453.469063}
+{"media_id": "M_EN_060_M", "operation": "modification", "audio_path": "audio/anchor/M_EN_060_M.flac", "duration_sec": 2181.282563}
+{"media_id": "M_ZH_001_D", "operation": "deletion", "audio_path": "audio/anchor/M_ZH_001_D.flac", "duration_sec": 2178.542625}
+{"media_id": "M_ZH_002_D", "operation": "deletion", "audio_path": "audio/anchor/M_ZH_002_D.flac", "duration_sec": 3353.173375}
+{"media_id": "M_ZH_003_A", "operation": "addition", "audio_path": "audio/anchor/M_ZH_003_A.flac", "duration_sec": 3454.548813}
+{"media_id": "M_ZH_004_A", "operation": "addition", "audio_path": "audio/anchor/M_ZH_004_A.flac", "duration_sec": 2739.049125}
+{"media_id": "M_ZH_005_A", "operation": "addition", "audio_path": "audio/anchor/M_ZH_005_A.flac", "duration_sec": 2914.77775}
+{"media_id": "M_ZH_006_A", "operation": "addition", "audio_path": "audio/anchor/M_ZH_006_A.flac", "duration_sec": 2259.046188}
+{"media_id": "M_ZH_007_M", "operation": "modification", "audio_path": "audio/anchor/M_ZH_007_M.flac", "duration_sec": 2937.997688}
+{"media_id": "M_ZH_008_A", "operation": "addition", "audio_path": "audio/anchor/M_ZH_008_A.flac", "duration_sec": 2690.194313}
+{"media_id": "M_ZH_009_D", "operation": "deletion", "audio_path": "audio/anchor/M_ZH_009_D.flac", "duration_sec": 2052.516313}
+{"media_id": "M_ZH_010_M", "operation": "modification", "audio_path": "audio/anchor/M_ZH_010_M.flac", "duration_sec": 1920.872875}
+{"media_id": "M_ZH_011_M", "operation": "modification", "audio_path": "audio/anchor/M_ZH_011_M.flac", "duration_sec": 1980.104875}
+{"media_id": "M_ZH_012_A", "operation": "addition", "audio_path": "audio/anchor/M_ZH_012_A.flac", "duration_sec": 3166.470438}
+{"media_id": "M_ZH_013_D", "operation": "deletion", "audio_path": "audio/anchor/M_ZH_013_D.flac", "duration_sec": 2551.9195}
+{"media_id": "M_ZH_014_M", "operation": "modification", "audio_path": "audio/anchor/M_ZH_014_M.flac", "duration_sec": 1827.318875}
+{"media_id": "M_ZH_015_M", "operation": "modification", "audio_path": "audio/anchor/M_ZH_015_M.flac", "duration_sec": 2809.75775}
+{"media_id": "M_ZH_016_D", "operation": "deletion", "audio_path": "audio/anchor/M_ZH_016_D.flac", "duration_sec": 2257.444}
+{"media_id": "M_ZH_017_A", "operation": "addition", "audio_path": "audio/anchor/M_ZH_017_A.flac", "duration_sec": 2068.735438}
+{"media_id": "M_ZH_018_D", "operation": "deletion", "audio_path": "audio/anchor/M_ZH_018_D.flac", "duration_sec": 2860.025063}
+{"media_id": "M_ZH_019_A", "operation": "addition", "audio_path": "audio/anchor/M_ZH_019_A.flac", "duration_sec": 2294.016}
+{"media_id": "M_ZH_020_D", "operation": "deletion", "audio_path": "audio/anchor/M_ZH_020_D.flac", "duration_sec": 2022.21425}
+{"media_id": "M_ZH_021_A", "operation": "addition", "audio_path": "audio/anchor/M_ZH_021_A.flac", "duration_sec": 3299.72975}
+{"media_id": "M_ZH_022_M", "operation": "modification", "audio_path": "audio/anchor/M_ZH_022_M.flac", "duration_sec": 2080.088375}
+{"media_id": "M_ZH_023_A", "operation": "addition", "audio_path": "audio/anchor/M_ZH_023_A.flac", "duration_sec": 2891.139813}
+{"media_id": "M_ZH_024_M", "operation": "modification", "audio_path": "audio/anchor/M_ZH_024_M.flac", "duration_sec": 2926.942625}
+{"media_id": "M_ZH_025_M", "operation": "modification", "audio_path": "audio/anchor/M_ZH_025_M.flac", "duration_sec": 3472.381688}
+{"media_id": "M_ZH_026_D", "operation": "deletion", "audio_path": "audio/anchor/M_ZH_026_D.flac", "duration_sec": 2870.114125}
+{"media_id": "M_ZH_027_M", "operation": "modification", "audio_path": "audio/anchor/M_ZH_027_M.flac", "duration_sec": 2085.802125}
+{"media_id": "M_ZH_028_M", "operation": "modification", "audio_path": "audio/anchor/M_ZH_028_M.flac", "duration_sec": 1882.17475}
+{"media_id": "M_ZH_029_D", "operation": "deletion", "audio_path": "audio/anchor/M_ZH_029_D.flac", "duration_sec": 2696.810688}
+{"media_id": "M_ZH_030_D", "operation": "deletion", "audio_path": "audio/anchor/M_ZH_030_D.flac", "duration_sec": 2506.24}
+{"media_id": "M_ZH_031_M", "operation": "modification", "audio_path": "audio/anchor/M_ZH_031_M.flac", "duration_sec": 3468.469125}
+{"media_id": "M_ZH_032_D", "operation": "deletion", "audio_path": "audio/anchor/M_ZH_032_D.flac", "duration_sec": 2725.012625}
+{"media_id": "M_ZH_033_A", "operation": "addition", "audio_path": "audio/anchor/M_ZH_033_A.flac", "duration_sec": 2695.442}
+{"media_id": "M_ZH_034_A", "operation": "addition", "audio_path": "audio/anchor/M_ZH_034_A.flac", "duration_sec": 1852.395188}
+{"media_id": "M_ZH_035_M", "operation": "modification", "audio_path": "audio/anchor/M_ZH_035_M.flac", "duration_sec": 2131.61425}
+{"media_id": "M_ZH_036_D", "operation": "deletion", "audio_path": "audio/anchor/M_ZH_036_D.flac", "duration_sec": 3040.235125}
+{"media_id": "M_ZH_037_A", "operation": "addition", "audio_path": "audio/anchor/M_ZH_037_A.flac", "duration_sec": 2175.849125}
+{"media_id": "M_ZH_038_M", "operation": "modification", "audio_path": "audio/anchor/M_ZH_038_M.flac", "duration_sec": 3495.833375}
+{"media_id": "M_ZH_039_D", "operation": "deletion", "audio_path": "audio/anchor/M_ZH_039_D.flac", "duration_sec": 1886.226625}
+{"media_id": "M_ZH_040_A", "operation": "addition", "audio_path": "audio/anchor/M_ZH_040_A.flac", "duration_sec": 2731.990313}
+{"media_id": "M_ZH_041_M", "operation": "modification", "audio_path": "audio/anchor/M_ZH_041_M.flac", "duration_sec": 2430.6065}
+{"media_id": "M_ZH_042_A", "operation": "addition", "audio_path": "audio/anchor/M_ZH_042_A.flac", "duration_sec": 2489.829313}
+{"media_id": "M_ZH_043_M", "operation": "modification", "audio_path": "audio/anchor/M_ZH_043_M.flac", "duration_sec": 2236.64}
+{"media_id": "M_ZH_044_D", "operation": "deletion", "audio_path": "audio/anchor/M_ZH_044_D.flac", "duration_sec": 3041.767625}
+{"media_id": "M_ZH_045_D", "operation": "deletion", "audio_path": "audio/anchor/M_ZH_045_D.flac", "duration_sec": 3000.180688}
+{"media_id": "M_ZH_046_A", "operation": "addition", "audio_path": "audio/anchor/M_ZH_046_A.flac", "duration_sec": 2470.405813}
+{"media_id": "M_ZH_047_M", "operation": "modification", "audio_path": "audio/anchor/M_ZH_047_M.flac", "duration_sec": 1832.008}
+{"media_id": "M_ZH_048_A", "operation": "addition", "audio_path": "audio/anchor/M_ZH_048_A.flac", "duration_sec": 1811.261}
+{"media_id": "M_ZH_049_D", "operation": "deletion", "audio_path": "audio/anchor/M_ZH_049_D.flac", "duration_sec": 2031.08}
+{"media_id": "M_ZH_050_A", "operation": "addition", "audio_path": "audio/anchor/M_ZH_050_A.flac", "duration_sec": 1863.076313}
+{"media_id": "M_ZH_051_D", "operation": "deletion", "audio_path": "audio/anchor/M_ZH_051_D.flac", "duration_sec": 3232.27575}
+{"media_id": "M_ZH_052_M", "operation": "modification", "audio_path": "audio/anchor/M_ZH_052_M.flac", "duration_sec": 2082.214625}
+{"media_id": "M_ZH_053_D", "operation": "deletion", "audio_path": "audio/anchor/M_ZH_053_D.flac", "duration_sec": 2783.68}
+{"media_id": "M_ZH_054_A", "operation": "addition", "audio_path": "audio/anchor/M_ZH_054_A.flac", "duration_sec": 3527.563938}
+{"media_id": "M_ZH_055_M", "operation": "modification", "audio_path": "audio/anchor/M_ZH_055_M.flac", "duration_sec": 1984.609563}
+{"media_id": "M_ZH_056_A", "operation": "addition", "audio_path": "audio/anchor/M_ZH_056_A.flac", "duration_sec": 2730.004938}
+{"media_id": "M_ZH_057_M", "operation": "modification", "audio_path": "audio/anchor/M_ZH_057_M.flac", "duration_sec": 2906.12}
+{"media_id": "M_ZH_058_M", "operation": "modification", "audio_path": "audio/anchor/M_ZH_058_M.flac", "duration_sec": 2768.16}
+{"media_id": "M_ZH_059_D", "operation": "deletion", "audio_path": "audio/anchor/M_ZH_059_D.flac", "duration_sec": 2384.039188}
+{"media_id": "M_ZH_060_D", "operation": "deletion", "audio_path": "audio/anchor/M_ZH_060_D.flac", "duration_sec": 2981.372563}

metadata/media/anchor/S.jsonl

@@ -0,0 +1,120 @@
+{"media_id": "S_EN_001_M", "operation": "modification", "audio_path": "audio/anchor/S_EN_001_M.flac", "duration_sec": 684.373375}
+{"media_id": "S_EN_002_D", "operation": "deletion", "audio_path": "audio/anchor/S_EN_002_D.flac", "duration_sec": 941.25575}
+{"media_id": "S_EN_003_M", "operation": "modification", "audio_path": "audio/anchor/S_EN_003_M.flac", "duration_sec": 749.400875}
+{"media_id": "S_EN_004_A", "operation": "addition", "audio_path": "audio/anchor/S_EN_004_A.flac", "duration_sec": 734.447188}
+{"media_id": "S_EN_005_D", "operation": "deletion", "audio_path": "audio/anchor/S_EN_005_D.flac", "duration_sec": 626.962}
+{"media_id": "S_EN_006_M", "operation": "modification", "audio_path": "audio/anchor/S_EN_006_M.flac", "duration_sec": 1058.655813}
+{"media_id": "S_EN_007_A", "operation": "addition", "audio_path": "audio/anchor/S_EN_007_A.flac", "duration_sec": 616.211188}
+{"media_id": "S_EN_008_D", "operation": "deletion", "audio_path": "audio/anchor/S_EN_008_D.flac", "duration_sec": 1728.15675}
+{"media_id": "S_EN_009_M", "operation": "modification", "audio_path": "audio/anchor/S_EN_009_M.flac", "duration_sec": 728.468063}
+{"media_id": "S_EN_010_A", "operation": "addition", "audio_path": "audio/anchor/S_EN_010_A.flac", "duration_sec": 1178.877125}
+{"media_id": "S_EN_011_D", "operation": "deletion", "audio_path": "audio/anchor/S_EN_011_D.flac", "duration_sec": 659.072}
+{"media_id": "S_EN_012_D", "operation": "deletion", "audio_path": "audio/anchor/S_EN_012_D.flac", "duration_sec": 600.170688}
+{"media_id": "S_EN_013_M", "operation": "modification", "audio_path": "audio/anchor/S_EN_013_M.flac", "duration_sec": 768.905625}
+{"media_id": "S_EN_014_A", "operation": "addition", "audio_path": "audio/anchor/S_EN_014_A.flac", "duration_sec": 877.12}
+{"media_id": "S_EN_015_A", "operation": "addition", "audio_path": "audio/anchor/S_EN_015_A.flac", "duration_sec": 651.79575}
+{"media_id": "S_EN_016_D", "operation": "deletion", "audio_path": "audio/anchor/S_EN_016_D.flac", "duration_sec": 1093.636688}
+{"media_id": "S_EN_017_M", "operation": "modification", "audio_path": "audio/anchor/S_EN_017_M.flac", "duration_sec": 984.944063}
+{"media_id": "S_EN_018_A", "operation": "addition", "audio_path": "audio/anchor/S_EN_018_A.flac", "duration_sec": 1046.082188}
+{"media_id": "S_EN_019_M", "operation": "modification", "audio_path": "audio/anchor/S_EN_019_M.flac", "duration_sec": 700.117375}
+{"media_id": "S_EN_020_M", "operation": "modification", "audio_path": "audio/anchor/S_EN_020_M.flac", "duration_sec": 1236.578688}
+{"media_id": "S_EN_021_D", "operation": "deletion", "audio_path": "audio/anchor/S_EN_021_D.flac", "duration_sec": 820.885375}
+{"media_id": "S_EN_022_A", "operation": "addition", "audio_path": "audio/anchor/S_EN_022_A.flac", "duration_sec": 1073.110313}
+{"media_id": "S_EN_023_A", "operation": "addition", "audio_path": "audio/anchor/S_EN_023_A.flac", "duration_sec": 1382.063375}
+{"media_id": "S_EN_024_D", "operation": "deletion", "audio_path": "audio/anchor/S_EN_024_D.flac", "duration_sec": 686.528}
+{"media_id": "S_EN_025_M", "operation": "modification", "audio_path": "audio/anchor/S_EN_025_M.flac", "duration_sec": 753.963563}
+{"media_id": "S_EN_026_M", "operation": "modification", "audio_path": "audio/anchor/S_EN_026_M.flac", "duration_sec": 754.567313}
+{"media_id": "S_EN_027_A", "operation": "addition", "audio_path": "audio/anchor/S_EN_027_A.flac", "duration_sec": 1522.102875}
+{"media_id": "S_EN_028_D", "operation": "deletion", "audio_path": "audio/anchor/S_EN_028_D.flac", "duration_sec": 826.375}
+{"media_id": "S_EN_029_A", "operation": "addition", "audio_path": "audio/anchor/S_EN_029_A.flac", "duration_sec": 862.50525}
+{"media_id": "S_EN_030_M", "operation": "modification", "audio_path": "audio/anchor/S_EN_030_M.flac", "duration_sec": 810.956938}
+{"media_id": "S_EN_031_D", "operation": "deletion", "audio_path": "audio/anchor/S_EN_031_D.flac", "duration_sec": 684.09475}
+{"media_id": "S_EN_032_A", "operation": "addition", "audio_path": "audio/anchor/S_EN_032_A.flac", "duration_sec": 881.237375}
+{"media_id": "S_EN_033_M", "operation": "modification", "audio_path": "audio/anchor/S_EN_033_M.flac", "duration_sec": 1237.008313}
+{"media_id": "S_EN_034_M", "operation": "modification", "audio_path": "audio/anchor/S_EN_034_M.flac", "duration_sec": 1280.81275}
+{"media_id": "S_EN_035_A", "operation": "addition", "audio_path": "audio/anchor/S_EN_035_A.flac", "duration_sec": 909.525438}
+{"media_id": "S_EN_036_D", "operation": "deletion", "audio_path": "audio/anchor/S_EN_036_D.flac", "duration_sec": 608.583438}
+{"media_id": "S_EN_037_M", "operation": "modification", "audio_path": "audio/anchor/S_EN_037_M.flac", "duration_sec": 1189.093938}
+{"media_id": "S_EN_038_M", "operation": "modification", "audio_path": "audio/anchor/S_EN_038_M.flac", "duration_sec": 627.240688}
+{"media_id": "S_EN_039_D", "operation": "deletion", "audio_path": "audio/anchor/S_EN_039_D.flac", "duration_sec": 1766.005313}
+{"media_id": "S_EN_040_D", "operation": "deletion", "audio_path": "audio/anchor/S_EN_040_D.flac", "duration_sec": 1529.602938}
+{"media_id": "S_EN_041_D", "operation": "deletion", "audio_path": "audio/anchor/S_EN_041_D.flac", "duration_sec": 1716.953125}
+{"media_id": "S_EN_042_A", "operation": "addition", "audio_path": "audio/anchor/S_EN_042_A.flac", "duration_sec": 600.096563}
+{"media_id": "S_EN_043_A", "operation": "addition", "audio_path": "audio/anchor/S_EN_043_A.flac", "duration_sec": 1743.7025}
+{"media_id": "S_EN_044_D", "operation": "deletion", "audio_path": "audio/anchor/S_EN_044_D.flac", "duration_sec": 856.955688}
+{"media_id": "S_EN_045_M", "operation": "modification", "audio_path": "audio/anchor/S_EN_045_M.flac", "duration_sec": 1450.922125}
+{"media_id": "S_EN_046_A", "operation": "addition", "audio_path": "audio/anchor/S_EN_046_A.flac", "duration_sec": 882.811125}
+{"media_id": "S_EN_047_M", "operation": "modification", "audio_path": "audio/anchor/S_EN_047_M.flac", "duration_sec": 667.991688}
+{"media_id": "S_EN_048_D", "operation": "deletion", "audio_path": "audio/anchor/S_EN_048_D.flac", "duration_sec": 899.343688}
+{"media_id": "S_EN_049_D", "operation": "deletion", "audio_path": "audio/anchor/S_EN_049_D.flac", "duration_sec": 911.552}
+{"media_id": "S_EN_050_M", "operation": "modification", "audio_path": "audio/anchor/S_EN_050_M.flac", "duration_sec": 923.864}
+{"media_id": "S_EN_051_D", "operation": "deletion", "audio_path": "audio/anchor/S_EN_051_D.flac", "duration_sec": 1114.395313}
+{"media_id": "S_EN_052_A", "operation": "addition", "audio_path": "audio/anchor/S_EN_052_A.flac", "duration_sec": 630.503125}
+{"media_id": "S_EN_053_M", "operation": "modification", "audio_path": "audio/anchor/S_EN_053_M.flac", "duration_sec": 639.84925}
+{"media_id": "S_EN_054_A", "operation": "addition", "audio_path": "audio/anchor/S_EN_054_A.flac", "duration_sec": 665.670813}
+{"media_id": "S_EN_055_A", "operation": "addition", "audio_path": "audio/anchor/S_EN_055_A.flac", "duration_sec": 682.14425}
+{"media_id": "S_EN_056_D", "operation": "deletion", "audio_path": "audio/anchor/S_EN_056_D.flac", "duration_sec": 600.32875}
+{"media_id": "S_EN_057_M", "operation": "modification", "audio_path": "audio/anchor/S_EN_057_M.flac", "duration_sec": 973.233938}
+{"media_id": "S_EN_058_A", "operation": "addition", "audio_path": "audio/anchor/S_EN_058_A.flac", "duration_sec": 1214.549375}
+{"media_id": "S_EN_059_A", "operation": "addition", "audio_path": "audio/anchor/S_EN_059_A.flac", "duration_sec": 765.845438}
+{"media_id": "S_EN_060_D", "operation": "deletion", "audio_path": "audio/anchor/S_EN_060_D.flac", "duration_sec": 674.841563}
+{"media_id": "S_ZH_001_M", "operation": "modification", "audio_path": "audio/anchor/S_ZH_001_M.flac", "duration_sec": 879.548688}
+{"media_id": "S_ZH_002_D", "operation": "deletion", "audio_path": "audio/anchor/S_ZH_002_D.flac", "duration_sec": 1375.422438}
+{"media_id": "S_ZH_003_A", "operation": "addition", "audio_path": "audio/anchor/S_ZH_003_A.flac", "duration_sec": 759.780188}
+{"media_id": "S_ZH_004_D", "operation": "deletion", "audio_path": "audio/anchor/S_ZH_004_D.flac", "duration_sec": 611.811}
+{"media_id": "S_ZH_005_M", "operation": "modification", "audio_path": "audio/anchor/S_ZH_005_M.flac", "duration_sec": 857.408}
+{"media_id": "S_ZH_006_D", "operation": "deletion", "audio_path": "audio/anchor/S_ZH_006_D.flac", "duration_sec": 1299.434688}
+{"media_id": "S_ZH_007_M", "operation": "modification", "audio_path": "audio/anchor/S_ZH_007_M.flac", "duration_sec": 1274.656875}
+{"media_id": "S_ZH_008_D", "operation": "deletion", "audio_path": "audio/anchor/S_ZH_008_D.flac", "duration_sec": 1310.580688}
+{"media_id": "S_ZH_009_A", "operation": "addition", "audio_path": "audio/anchor/S_ZH_009_A.flac", "duration_sec": 1682.192875}
+{"media_id": "S_ZH_010_D", "operation": "deletion", "audio_path": "audio/anchor/S_ZH_010_D.flac", "duration_sec": 601.443313}
+{"media_id": "S_ZH_011_M", "operation": "modification", "audio_path": "audio/anchor/S_ZH_011_M.flac", "duration_sec": 610.575625}
+{"media_id": "S_ZH_012_D", "operation": "deletion", "audio_path": "audio/anchor/S_ZH_012_D.flac", "duration_sec": 1780.065}
+{"media_id": "S_ZH_013_A", "operation": "addition", "audio_path": "audio/anchor/S_ZH_013_A.flac", "duration_sec": 1007.786688}
+{"media_id": "S_ZH_014_A", "operation": "addition", "audio_path": "audio/anchor/S_ZH_014_A.flac", "duration_sec": 611.230563}
+{"media_id": "S_ZH_015_D", "operation": "deletion", "audio_path": "audio/anchor/S_ZH_015_D.flac", "duration_sec": 916.60775}
+{"media_id": "S_ZH_016_M", "operation": "modification", "audio_path": "audio/anchor/S_ZH_016_M.flac", "duration_sec": 657.138313}
+{"media_id": "S_ZH_017_M", "operation": "modification", "audio_path": "audio/anchor/S_ZH_017_M.flac", "duration_sec": 975.332813}
+{"media_id": "S_ZH_018_M", "operation": "modification", "audio_path": "audio/anchor/S_ZH_018_M.flac", "duration_sec": 1703.125625}
+{"media_id": "S_ZH_019_A", "operation": "addition", "audio_path": "audio/anchor/S_ZH_019_A.flac", "duration_sec": 1501.76}
+{"media_id": "S_ZH_020_A", "operation": "addition", "audio_path": "audio/anchor/S_ZH_020_A.flac", "duration_sec": 819.060688}
+{"media_id": "S_ZH_021_D", "operation": "deletion", "audio_path": "audio/anchor/S_ZH_021_D.flac", "duration_sec": 713.88}
+{"media_id": "S_ZH_022_M", "operation": "modification", "audio_path": "audio/anchor/S_ZH_022_M.flac", "duration_sec": 606.249813}
+{"media_id": "S_ZH_023_M", "operation": "modification", "audio_path": "audio/anchor/S_ZH_023_M.flac", "duration_sec": 1497.420125}
+{"media_id": "S_ZH_024_D", "operation": "deletion", "audio_path": "audio/anchor/S_ZH_024_D.flac", "duration_sec": 624.732938}
+{"media_id": "S_ZH_025_A", "operation": "addition", "audio_path": "audio/anchor/S_ZH_025_A.flac", "duration_sec": 699.733375}
+{"media_id": "S_ZH_026_D", "operation": "deletion", "audio_path": "audio/anchor/S_ZH_026_D.flac", "duration_sec": 841.472063}
+{"media_id": "S_ZH_027_D", "operation": "deletion", "audio_path": "audio/anchor/S_ZH_027_D.flac", "duration_sec": 1291.075938}
+{"media_id": "S_ZH_028_A", "operation": "addition", "audio_path": "audio/anchor/S_ZH_028_A.flac", "duration_sec": 863.201875}
+{"media_id": "S_ZH_029_M", "operation": "modification", "audio_path": "audio/anchor/S_ZH_029_M.flac", "duration_sec": 1104.3875}
+{"media_id": "S_ZH_030_A", "operation": "addition", "audio_path": "audio/anchor/S_ZH_030_A.flac", "duration_sec": 767.829375}
+{"media_id": "S_ZH_031_D", "operation": "deletion", "audio_path": "audio/anchor/S_ZH_031_D.flac", "duration_sec": 1187.433688}
+{"media_id": "S_ZH_032_D", "operation": "deletion", "audio_path": "audio/anchor/S_ZH_032_D.flac", "duration_sec": 1044.178188}
+{"media_id": "S_ZH_033_M", "operation": "modification", "audio_path": "audio/anchor/S_ZH_033_M.flac", "duration_sec": 1325.511125}
+{"media_id": "S_ZH_034_M", "operation": "modification", "audio_path": "audio/anchor/S_ZH_034_M.flac", "duration_sec": 838.310063}
+{"media_id": "S_ZH_035_A", "operation": "addition", "audio_path": "audio/anchor/S_ZH_035_A.flac", "duration_sec": 607.259875}
+{"media_id": "S_ZH_036_A", "operation": "addition", "audio_path": "audio/anchor/S_ZH_036_A.flac", "duration_sec": 784.404938}
+{"media_id": "S_ZH_037_D", "operation": "deletion", "audio_path": "audio/anchor/S_ZH_037_D.flac", "duration_sec": 737.001375}
+{"media_id": "S_ZH_038_M", "operation": "modification", "audio_path": "audio/anchor/S_ZH_038_M.flac", "duration_sec": 1519.550063}
+{"media_id": "S_ZH_039_A", "operation": "addition", "audio_path": "audio/anchor/S_ZH_039_A.flac", "duration_sec": 1710.68}
+{"media_id": "S_ZH_040_D", "operation": "deletion", "audio_path": "audio/anchor/S_ZH_040_D.flac", "duration_sec": 1044.433563}
+{"media_id": "S_ZH_041_M", "operation": "modification", "audio_path": "audio/anchor/S_ZH_041_M.flac", "duration_sec": 1043.574438}
+{"media_id": "S_ZH_042_A", "operation": "addition", "audio_path": "audio/anchor/S_ZH_042_A.flac", "duration_sec": 1763.207313}
+{"media_id": "S_ZH_043_A", "operation": "addition", "audio_path": "audio/anchor/S_ZH_043_A.flac", "duration_sec": 744.350563}
+{"media_id": "S_ZH_044_M", "operation": "modification", "audio_path": "audio/anchor/S_ZH_044_M.flac", "duration_sec": 795.394625}
+{"media_id": "S_ZH_045_A", "operation": "addition", "audio_path": "audio/anchor/S_ZH_045_A.flac", "duration_sec": 870.771563}
+{"media_id": "S_ZH_046_D", "operation": "deletion", "audio_path": "audio/anchor/S_ZH_046_D.flac", "duration_sec": 674.528125}
+{"media_id": "S_ZH_047_M", "operation": "modification", "audio_path": "audio/anchor/S_ZH_047_M.flac", "duration_sec": 992.1575}
+{"media_id": "S_ZH_048_A", "operation": "addition", "audio_path": "audio/anchor/S_ZH_048_A.flac", "duration_sec": 1244.310938}
+{"media_id": "S_ZH_049_D", "operation": "deletion", "audio_path": "audio/anchor/S_ZH_049_D.flac", "duration_sec": 659.284188}
+{"media_id": "S_ZH_050_M", "operation": "modification", "audio_path": "audio/anchor/S_ZH_050_M.flac", "duration_sec": 1398.421813}
+{"media_id": "S_ZH_051_M", "operation": "modification", "audio_path": "audio/anchor/S_ZH_051_M.flac", "duration_sec": 1713.365625}
+{"media_id": "S_ZH_052_D", "operation": "deletion", "audio_path": "audio/anchor/S_ZH_052_D.flac", "duration_sec": 775.94125}
+{"media_id": "S_ZH_053_D", "operation": "deletion", "audio_path": "audio/anchor/S_ZH_053_D.flac", "duration_sec": 1714.468625}
+{"media_id": "S_ZH_054_A", "operation": "addition", "audio_path": "audio/anchor/S_ZH_054_A.flac", "duration_sec": 809.24}
+{"media_id": "S_ZH_055_A", "operation": "addition", "audio_path": "audio/anchor/S_ZH_055_A.flac", "duration_sec": 1703.488}
+{"media_id": "S_ZH_056_A", "operation": "addition", "audio_path": "audio/anchor/S_ZH_056_A.flac", "duration_sec": 609.361313}
+{"media_id": "S_ZH_057_A", "operation": "addition", "audio_path": "audio/anchor/S_ZH_057_A.flac", "duration_sec": 637.085938}
+{"media_id": "S_ZH_058_M", "operation": "modification", "audio_path": "audio/anchor/S_ZH_058_M.flac", "duration_sec": 833.967875}
+{"media_id": "S_ZH_059_M", "operation": "modification", "audio_path": "audio/anchor/S_ZH_059_M.flac", "duration_sec": 868.757375}
+{"media_id": "S_ZH_060_D", "operation": "deletion", "audio_path": "audio/anchor/S_ZH_060_D.flac", "duration_sec": 663.92}

metadata/media/native/L.jsonl

@@ -0,0 +1,120 @@
+{"media_id": "L_EN_001", "genre": "discussion", "topic": "arts", "language": "en", "duration_sec": 4358.88475, "audio_path": "audio/native/L_EN_001.flac"}
+{"media_id": "L_EN_002", "genre": "drama_variety", "topic": "entertainment", "language": "en", "duration_sec": 4945.711063, "audio_path": "audio/native/L_EN_002.flac"}
+{"media_id": "L_EN_003", "genre": "live_stream", "topic": "technology", "language": "en", "duration_sec": 3660.231125, "audio_path": "audio/native/L_EN_003.flac"}
+{"media_id": "L_EN_004", "genre": "lecture", "topic": "education", "language": "en", "duration_sec": 5220.448, "audio_path": "audio/native/L_EN_004.flac"}
+{"media_id": "L_EN_005", "genre": "lecture", "topic": "business", "language": "en", "duration_sec": 5220.844313, "audio_path": "audio/native/L_EN_005.flac"}
+{"media_id": "L_EN_006", "genre": "commentary", "topic": "lifestyle", "language": "en", "duration_sec": 5714.605, "audio_path": "audio/native/L_EN_006.flac"}
+{"media_id": "L_EN_007", "genre": "live_stream", "topic": "sports", "language": "en", "duration_sec": 4755.81825, "audio_path": "audio/native/L_EN_007.flac"}
+{"media_id": "L_EN_008", "genre": "commentary", "topic": "arts", "language": "en", "duration_sec": 7826.007125, "audio_path": "audio/native/L_EN_008.flac"}
+{"media_id": "L_EN_009", "genre": "lecture", "topic": "lifestyle", "language": "en", "duration_sec": 3946.138438, "audio_path": "audio/native/L_EN_009.flac"}
+{"media_id": "L_EN_010", "genre": "documentary", "topic": "education", "language": "en", "duration_sec": 4087.73375, "audio_path": "audio/native/L_EN_010.flac"}
+{"media_id": "L_EN_011", "genre": "drama_variety", "topic": "entertainment", "language": "en", "duration_sec": 8315.147063, "audio_path": "audio/native/L_EN_011.flac"}
+{"media_id": "L_EN_012", "genre": "discussion", "topic": "lifestyle", "language": "en", "duration_sec": 3879.24175, "audio_path": "audio/native/L_EN_012.flac"}
+{"media_id": "L_EN_013", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 6221.09025, "audio_path": "audio/native/L_EN_013.flac"}
+{"media_id": "L_EN_014", "genre": "vlog", "topic": "arts", "language": "en", "duration_sec": 5581.682375, "audio_path": "audio/native/L_EN_014.flac"}
+{"media_id": "L_EN_015", "genre": "lecture", "topic": "health", "language": "en", "duration_sec": 3641.353313, "audio_path": "audio/native/L_EN_015.flac"}
+{"media_id": "L_EN_016", "genre": "discussion", "topic": "sports", "language": "en", "duration_sec": 4169.409938, "audio_path": "audio/native/L_EN_016.flac"}
+{"media_id": "L_EN_017", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 4284.824688, "audio_path": "audio/native/L_EN_017.flac"}
+{"media_id": "L_EN_018", "genre": "drama_variety", "topic": "entertainment", "language": "en", "duration_sec": 4372.363938, "audio_path": "audio/native/L_EN_018.flac"}
+{"media_id": "L_EN_019", "genre": "discussion", "topic": "arts", "language": "en", "duration_sec": 4021.510438, "audio_path": "audio/native/L_EN_019.flac"}
+{"media_id": "L_EN_020", "genre": "discussion", "topic": "technology", "language": "en", "duration_sec": 6449.899688, "audio_path": "audio/native/L_EN_020.flac"}
+{"media_id": "L_EN_021", "genre": "drama_variety", "topic": "entertainment", "language": "en", "duration_sec": 7624.701688, "audio_path": "audio/native/L_EN_021.flac"}
+{"media_id": "L_EN_022", "genre": "discussion", "topic": "gaming", "language": "en", "duration_sec": 5067.302375, "audio_path": "audio/native/L_EN_022.flac"}
+{"media_id": "L_EN_023", "genre": "vlog", "topic": "lifestyle", "language": "en", "duration_sec": 4613.12, "audio_path": "audio/native/L_EN_023.flac"}
+{"media_id": "L_EN_024", "genre": "discussion", "topic": "education", "language": "en", "duration_sec": 5038.84, "audio_path": "audio/native/L_EN_024.flac"}
+{"media_id": "L_EN_025", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 4304.042688, "audio_path": "audio/native/L_EN_025.flac"}
+{"media_id": "L_EN_026", "genre": "lecture", "topic": "business", "language": "en", "duration_sec": 3689.975875, "audio_path": "audio/native/L_EN_026.flac"}
+{"media_id": "L_EN_027", "genre": "documentary", "topic": "arts", "language": "en", "duration_sec": 5418.132625, "audio_path": "audio/native/L_EN_027.flac"}
+{"media_id": "L_EN_028", "genre": "commentary", "topic": "entertainment", "language": "en", "duration_sec": 3670.134438, "audio_path": "audio/native/L_EN_028.flac"}
+{"media_id": "L_EN_029", "genre": "documentary", "topic": "education", "language": "en", "duration_sec": 6958.521188, "audio_path": "audio/native/L_EN_029.flac"}
+{"media_id": "L_EN_030", "genre": "vlog", "topic": "lifestyle", "language": "en", "duration_sec": 5032.228625, "audio_path": "audio/native/L_EN_030.flac"}
+{"media_id": "L_EN_031", "genre": "lecture", "topic": "technology", "language": "en", "duration_sec": 4311.388313, "audio_path": "audio/native/L_EN_031.flac"}
+{"media_id": "L_EN_032", "genre": "discussion", "topic": "lifestyle", "language": "en", "duration_sec": 7956.201375, "audio_path": "audio/native/L_EN_032.flac"}
+{"media_id": "L_EN_033", "genre": "discussion", "topic": "arts", "language": "en", "duration_sec": 4695.875938, "audio_path": "audio/native/L_EN_033.flac"}
+{"media_id": "L_EN_034", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 4496.033438, "audio_path": "audio/native/L_EN_034.flac"}
+{"media_id": "L_EN_035", "genre": "lecture", "topic": "arts", "language": "en", "duration_sec": 7024.616813, "audio_path": "audio/native/L_EN_035.flac"}
+{"media_id": "L_EN_036", "genre": "discussion", "topic": "health", "language": "en", "duration_sec": 5224.524688, "audio_path": "audio/native/L_EN_036.flac"}
+{"media_id": "L_EN_037", "genre": "discussion", "topic": "business", "language": "en", "duration_sec": 3759.381375, "audio_path": "audio/native/L_EN_037.flac"}
+{"media_id": "L_EN_038", "genre": "drama_variety", "topic": "entertainment", "language": "en", "duration_sec": 6372.99525, "audio_path": "audio/native/L_EN_038.flac"}
+{"media_id": "L_EN_039", "genre": "live_stream", "topic": "arts", "language": "en", "duration_sec": 5303.484125, "audio_path": "audio/native/L_EN_039.flac"}
+{"media_id": "L_EN_040", "genre": "commentary", "topic": "entertainment", "language": "en", "duration_sec": 4635.376375, "audio_path": "audio/native/L_EN_040.flac"}
+{"media_id": "L_EN_041", "genre": "drama_variety", "topic": "entertainment", "language": "en", "duration_sec": 4956.461875, "audio_path": "audio/native/L_EN_041.flac"}
+{"media_id": "L_EN_042", "genre": "drama_variety", "topic": "entertainment", "language": "en", "duration_sec": 5462.912, "audio_path": "audio/native/L_EN_042.flac"}
+{"media_id": "L_EN_043", "genre": "live_stream", "topic": "sports", "language": "en", "duration_sec": 9514.283563, "audio_path": "audio/native/L_EN_043.flac"}
+{"media_id": "L_EN_044", "genre": "vlog", "topic": "lifestyle", "language": "en", "duration_sec": 4337.359875, "audio_path": "audio/native/L_EN_044.flac"}
+{"media_id": "L_EN_045", "genre": "discussion", "topic": "arts", "language": "en", "duration_sec": 8953.335875, "audio_path": "audio/native/L_EN_045.flac"}
+{"media_id": "L_EN_046", "genre": "commentary", "topic": "lifestyle", "language": "en", "duration_sec": 4351.605313, "audio_path": "audio/native/L_EN_046.flac"}
+{"media_id": "L_EN_047", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 3906.333375, "audio_path": "audio/native/L_EN_047.flac"}
+{"media_id": "L_EN_048", "genre": "drama_variety", "topic": "entertainment", "language": "en", "duration_sec": 6574.08, "audio_path": "audio/native/L_EN_048.flac"}
+{"media_id": "L_EN_049", "genre": "discussion", "topic": "health", "language": "en", "duration_sec": 7109.079375, "audio_path": "audio/native/L_EN_049.flac"}
+{"media_id": "L_EN_050", "genre": "lecture", "topic": "technology", "language": "en", "duration_sec": 7507.84, "audio_path": "audio/native/L_EN_050.flac"}
+{"media_id": "L_EN_051", "genre": "discussion", "topic": "sports", "language": "en", "duration_sec": 4138.875688, "audio_path": "audio/native/L_EN_051.flac"}
+{"media_id": "L_EN_052", "genre": "documentary", "topic": "education", "language": "en", "duration_sec": 5943.04, "audio_path": "audio/native/L_EN_052.flac"}
+{"media_id": "L_EN_053", "genre": "vlog", "topic": "lifestyle", "language": "en", "duration_sec": 8356.992, "audio_path": "audio/native/L_EN_053.flac"}
+{"media_id": "L_EN_054", "genre": "drama_variety", "topic": "entertainment", "language": "en", "duration_sec": 4773.488625, "audio_path": "audio/native/L_EN_054.flac"}
+{"media_id": "L_EN_055", "genre": "documentary", "topic": "arts", "language": "en", "duration_sec": 5249.103, "audio_path": "audio/native/L_EN_055.flac"}
+{"media_id": "L_EN_056", "genre": "lecture", "topic": "technology", "language": "en", "duration_sec": 3679.341188, "audio_path": "audio/native/L_EN_056.flac"}
+{"media_id": "L_EN_057", "genre": "discussion", "topic": "sports", "language": "en", "duration_sec": 3951.223625, "audio_path": "audio/native/L_EN_057.flac"}
+{"media_id": "L_EN_058", "genre": "live_stream", "topic": "sports", "language": "en", "duration_sec": 8480.066813, "audio_path": "audio/native/L_EN_058.flac"}
+{"media_id": "L_EN_059", "genre": "lecture", "topic": "business", "language": "en", "duration_sec": 3648.490688, "audio_path": "audio/native/L_EN_059.flac"}
+{"media_id": "L_EN_060", "genre": "vlog", "topic": "lifestyle", "language": "en", "duration_sec": 7897.234313, "audio_path": "audio/native/L_EN_060.flac"}
+{"media_id": "L_ZH_001", "genre": "live_stream", "topic": "business", "language": "zh", "duration_sec": 9813.147625, "audio_path": "audio/native/L_ZH_001.flac"}
+{"media_id": "L_ZH_002", "genre": "lecture", "topic": "technology", "language": "zh", "duration_sec": 8349.884125, "audio_path": "audio/native/L_ZH_002.flac"}
+{"media_id": "L_ZH_003", "genre": "discussion", "topic": "business", "language": "zh", "duration_sec": 3888.018875, "audio_path": "audio/native/L_ZH_003.flac"}
+{"media_id": "L_ZH_004", "genre": "lecture", "topic": "education", "language": "zh", "duration_sec": 3642.584, "audio_path": "audio/native/L_ZH_004.flac"}
+{"media_id": "L_ZH_005", "genre": "lecture", "topic": "lifestyle", "language": "zh", "duration_sec": 4143.624188, "audio_path": "audio/native/L_ZH_005.flac"}
+{"media_id": "L_ZH_006", "genre": "live_stream", "topic": "arts", "language": "zh", "duration_sec": 8349.013375, "audio_path": "audio/native/L_ZH_006.flac"}
+{"media_id": "L_ZH_007", "genre": "lecture", "topic": "education", "language": "zh", "duration_sec": 4050.686313, "audio_path": "audio/native/L_ZH_007.flac"}
+{"media_id": "L_ZH_008", "genre": "lecture", "topic": "education", "language": "zh", "duration_sec": 4408.169125, "audio_path": "audio/native/L_ZH_008.flac"}
+{"media_id": "L_ZH_009", "genre": "lecture", "topic": "technology", "language": "zh", "duration_sec": 4401.563, "audio_path": "audio/native/L_ZH_009.flac"}
+{"media_id": "L_ZH_010", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 3632.135, "audio_path": "audio/native/L_ZH_010.flac"}
+{"media_id": "L_ZH_011", "genre": "drama_variety", "topic": "lifestyle", "language": "zh", "duration_sec": 4511.126375, "audio_path": "audio/native/L_ZH_011.flac"}
+{"media_id": "L_ZH_012", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 5157.610688, "audio_path": "audio/native/L_ZH_012.flac"}
+{"media_id": "L_ZH_013", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 8343.133375, "audio_path": "audio/native/L_ZH_013.flac"}
+{"media_id": "L_ZH_014", "genre": "lecture", "topic": "education", "language": "zh", "duration_sec": 7498.094938, "audio_path": "audio/native/L_ZH_014.flac"}
+{"media_id": "L_ZH_015", "genre": "lecture", "topic": "technology", "language": "zh", "duration_sec": 4377.72775, "audio_path": "audio/native/L_ZH_015.flac"}
+{"media_id": "L_ZH_016", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 8465.171188, "audio_path": "audio/native/L_ZH_016.flac"}
+{"media_id": "L_ZH_017", "genre": "discussion", "topic": "arts", "language": "zh", "duration_sec": 7279.5255, "audio_path": "audio/native/L_ZH_017.flac"}
+{"media_id": "L_ZH_018", "genre": "lecture", "topic": "education", "language": "zh", "duration_sec": 6272.49925, "audio_path": "audio/native/L_ZH_018.flac"}
+{"media_id": "L_ZH_019", "genre": "live_stream", "topic": "entertainment", "language": "zh", "duration_sec": 4458.208125, "audio_path": "audio/native/L_ZH_019.flac"}
+{"media_id": "L_ZH_020", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 5586.001313, "audio_path": "audio/native/L_ZH_020.flac"}
+{"media_id": "L_ZH_021", "genre": "drama_variety", "topic": "lifestyle", "language": "zh", "duration_sec": 5064.063188, "audio_path": "audio/native/L_ZH_021.flac"}
+{"media_id": "L_ZH_022", "genre": "discussion", "topic": "arts", "language": "zh", "duration_sec": 3885.604, "audio_path": "audio/native/L_ZH_022.flac"}
+{"media_id": "L_ZH_023", "genre": "documentary", "topic": "lifestyle", "language": "zh", "duration_sec": 3650.153688, "audio_path": "audio/native/L_ZH_023.flac"}
+{"media_id": "L_ZH_024", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 5419.920563, "audio_path": "audio/native/L_ZH_024.flac"}
+{"media_id": "L_ZH_025", "genre": "discussion", "topic": "arts", "language": "zh", "duration_sec": 7500.591063, "audio_path": "audio/native/L_ZH_025.flac"}
+{"media_id": "L_ZH_026", "genre": "discussion", "topic": "health", "language": "zh", "duration_sec": 5460.66, "audio_path": "audio/native/L_ZH_026.flac"}
+{"media_id": "L_ZH_027", "genre": "live_stream", "topic": "lifestyle", "language": "zh", "duration_sec": 5376.213375, "audio_path": "audio/native/L_ZH_027.flac"}
+{"media_id": "L_ZH_028", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 4295.7265, "audio_path": "audio/native/L_ZH_028.flac"}
+{"media_id": "L_ZH_029", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 3846.745438, "audio_path": "audio/native/L_ZH_029.flac"}
+{"media_id": "L_ZH_030", "genre": "live_stream", "topic": "entertainment", "language": "zh", "duration_sec": 5296.076938, "audio_path": "audio/native/L_ZH_030.flac"}
+{"media_id": "L_ZH_031", "genre": "discussion", "topic": "health", "language": "zh", "duration_sec": 5031.274688, "audio_path": "audio/native/L_ZH_031.flac"}
+{"media_id": "L_ZH_032", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 4080.6865, "audio_path": "audio/native/L_ZH_032.flac"}
+{"media_id": "L_ZH_033", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 4603.634688, "audio_path": "audio/native/L_ZH_033.flac"}
+{"media_id": "L_ZH_034", "genre": "discussion", "topic": "sports", "language": "zh", "duration_sec": 5012.050438, "audio_path": "audio/native/L_ZH_034.flac"}
+{"media_id": "L_ZH_035", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 5695.019, "audio_path": "audio/native/L_ZH_035.flac"}
+{"media_id": "L_ZH_036", "genre": "discussion", "topic": "entertainment", "language": "zh", "duration_sec": 7525.033375, "audio_path": "audio/native/L_ZH_036.flac"}
+{"media_id": "L_ZH_037", "genre": "lecture", "topic": "education", "language": "zh", "duration_sec": 5908.689, "audio_path": "audio/native/L_ZH_037.flac"}
+{"media_id": "L_ZH_038", "genre": "live_stream", "topic": "business", "language": "zh", "duration_sec": 4632.381, "audio_path": "audio/native/L_ZH_038.flac"}
+{"media_id": "L_ZH_039", "genre": "documentary", "topic": "lifestyle", "language": "zh", "duration_sec": 5557.661375, "audio_path": "audio/native/L_ZH_039.flac"}
+{"media_id": "L_ZH_040", "genre": "discussion", "topic": "arts", "language": "zh", "duration_sec": 4594.544063, "audio_path": "audio/native/L_ZH_040.flac"}
+{"media_id": "L_ZH_041", "genre": "discussion", "topic": "lifestyle", "language": "zh", "duration_sec": 3899.4315, "audio_path": "audio/native/L_ZH_041.flac"}
+{"media_id": "L_ZH_042", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 4798.9145, "audio_path": "audio/native/L_ZH_042.flac"}
+{"media_id": "L_ZH_043", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 4024.389688, "audio_path": "audio/native/L_ZH_043.flac"}
+{"media_id": "L_ZH_044", "genre": "documentary", "topic": "arts", "language": "zh", "duration_sec": 5494.700438, "audio_path": "audio/native/L_ZH_044.flac"}
+{"media_id": "L_ZH_045", "genre": "lecture", "topic": "business", "language": "zh", "duration_sec": 3848.042688, "audio_path": "audio/native/L_ZH_045.flac"}
+{"media_id": "L_ZH_046", "genre": "lecture", "topic": "education", "language": "zh", "duration_sec": 3868.223875, "audio_path": "audio/native/L_ZH_046.flac"}
+{"media_id": "L_ZH_047", "genre": "live_stream", "topic": "gaming", "language": "zh", "duration_sec": 8786.953313, "audio_path": "audio/native/L_ZH_047.flac"}
+{"media_id": "L_ZH_048", "genre": "lecture", "topic": "business", "language": "zh", "duration_sec": 3742.069875, "audio_path": "audio/native/L_ZH_048.flac"}
+{"media_id": "L_ZH_049", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 4950.564, "audio_path": "audio/native/L_ZH_049.flac"}
+{"media_id": "L_ZH_050", "genre": "drama_variety", "topic": "business", "language": "zh", "duration_sec": 6136.883125, "audio_path": "audio/native/L_ZH_050.flac"}
+{"media_id": "L_ZH_051", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 4917.72, "audio_path": "audio/native/L_ZH_051.flac"}
+{"media_id": "L_ZH_052", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 5173.44075, "audio_path": "audio/native/L_ZH_052.flac"}
+{"media_id": "L_ZH_053", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 4890.28, "audio_path": "audio/native/L_ZH_053.flac"}
+{"media_id": "L_ZH_054", "genre": "discussion", "topic": "technology", "language": "zh", "duration_sec": 5530.076063, "audio_path": "audio/native/L_ZH_054.flac"}
+{"media_id": "L_ZH_055", "genre": "discussion", "topic": "sports", "language": "zh", "duration_sec": 4024.668313, "audio_path": "audio/native/L_ZH_055.flac"}
+{"media_id": "L_ZH_056", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 5340.345813, "audio_path": "audio/native/L_ZH_056.flac"}
+{"media_id": "L_ZH_057", "genre": "drama_variety", "topic": "arts", "language": "zh", "duration_sec": 3858.146438, "audio_path": "audio/native/L_ZH_057.flac"}
+{"media_id": "L_ZH_058", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 3862.08, "audio_path": "audio/native/L_ZH_058.flac"}
+{"media_id": "L_ZH_059", "genre": "drama_variety", "topic": "arts", "language": "zh", "duration_sec": 5165.673688, "audio_path": "audio/native/L_ZH_059.flac"}
+{"media_id": "L_ZH_060", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 9538.8735, "audio_path": "audio/native/L_ZH_060.flac"}

metadata/media/native/M.jsonl

@@ -0,0 +1,120 @@
+{"media_id": "M_EN_001", "genre": "discussion", "topic": "business", "language": "en", "duration_sec": 1902.561875, "audio_path": "audio/native/M_EN_001.flac"}
+{"media_id": "M_EN_002", "genre": "discussion", "topic": "business", "language": "en", "duration_sec": 2300.906688, "audio_path": "audio/native/M_EN_002.flac"}
+{"media_id": "M_EN_003", "genre": "drama_variety", "topic": "entertainment", "language": "en", "duration_sec": 1981.35875, "audio_path": "audio/native/M_EN_003.flac"}
+{"media_id": "M_EN_004", "genre": "lecture", "topic": "technology", "language": "en", "duration_sec": 3538.272, "audio_path": "audio/native/M_EN_004.flac"}
+{"media_id": "M_EN_005", "genre": "discussion", "topic": "education", "language": "en", "duration_sec": 3346.090688, "audio_path": "audio/native/M_EN_005.flac"}
+{"media_id": "M_EN_006", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 2407.317375, "audio_path": "audio/native/M_EN_006.flac"}
+{"media_id": "M_EN_007", "genre": "lecture", "topic": "health", "language": "en", "duration_sec": 2576.300438, "audio_path": "audio/native/M_EN_007.flac"}
+{"media_id": "M_EN_008", "genre": "discussion", "topic": "education", "language": "en", "duration_sec": 2294.178, "audio_path": "audio/native/M_EN_008.flac"}
+{"media_id": "M_EN_009", "genre": "vlog", "topic": "lifestyle", "language": "en", "duration_sec": 1823.01025, "audio_path": "audio/native/M_EN_009.flac"}
+{"media_id": "M_EN_010", "genre": "drama_variety", "topic": "entertainment", "language": "en", "duration_sec": 2192.184313, "audio_path": "audio/native/M_EN_010.flac"}
+{"media_id": "M_EN_011", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 3136.493438, "audio_path": "audio/native/M_EN_011.flac"}
+{"media_id": "M_EN_012", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 1861.892125, "audio_path": "audio/native/M_EN_012.flac"}
+{"media_id": "M_EN_013", "genre": "discussion", "topic": "technology", "language": "en", "duration_sec": 2446.01325, "audio_path": "audio/native/M_EN_013.flac"}
+{"media_id": "M_EN_014", "genre": "discussion", "topic": "business", "language": "en", "duration_sec": 3290.012188, "audio_path": "audio/native/M_EN_014.flac"}
+{"media_id": "M_EN_015", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 2590.615563, "audio_path": "audio/native/M_EN_015.flac"}
+{"media_id": "M_EN_016", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 2610.689188, "audio_path": "audio/native/M_EN_016.flac"}
+{"media_id": "M_EN_017", "genre": "vlog", "topic": "lifestyle", "language": "en", "duration_sec": 2042.334375, "audio_path": "audio/native/M_EN_017.flac"}
+{"media_id": "M_EN_018", "genre": "lecture", "topic": "lifestyle", "language": "en", "duration_sec": 2502.442688, "audio_path": "audio/native/M_EN_018.flac"}
+{"media_id": "M_EN_019", "genre": "commentary", "topic": "entertainment", "language": "en", "duration_sec": 2349.139625, "audio_path": "audio/native/M_EN_019.flac"}
+{"media_id": "M_EN_020", "genre": "discussion", "topic": "entertainment", "language": "en", "duration_sec": 2483.757313, "audio_path": "audio/native/M_EN_020.flac"}
+{"media_id": "M_EN_021", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 3587.831313, "audio_path": "audio/native/M_EN_021.flac"}
+{"media_id": "M_EN_022", "genre": "drama_variety", "topic": "entertainment", "language": "en", "duration_sec": 1830.037375, "audio_path": "audio/native/M_EN_022.flac"}
+{"media_id": "M_EN_023", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 2458.145688, "audio_path": "audio/native/M_EN_023.flac"}
+{"media_id": "M_EN_024", "genre": "vlog", "topic": "lifestyle", "language": "en", "duration_sec": 2002.517375, "audio_path": "audio/native/M_EN_024.flac"}
+{"media_id": "M_EN_025", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 2530.46425, "audio_path": "audio/native/M_EN_025.flac"}
+{"media_id": "M_EN_026", "genre": "documentary", "topic": "business", "language": "en", "duration_sec": 2278.411625, "audio_path": "audio/native/M_EN_026.flac"}
+{"media_id": "M_EN_027", "genre": "drama_variety", "topic": "entertainment", "language": "en", "duration_sec": 1974.218625, "audio_path": "audio/native/M_EN_027.flac"}
+{"media_id": "M_EN_028", "genre": "vlog", "topic": "sports", "language": "en", "duration_sec": 1813.525375, "audio_path": "audio/native/M_EN_028.flac"}
+{"media_id": "M_EN_029", "genre": "drama_variety", "topic": "entertainment", "language": "en", "duration_sec": 1910.9675, "audio_path": "audio/native/M_EN_029.flac"}
+{"media_id": "M_EN_030", "genre": "discussion", "topic": "business", "language": "en", "duration_sec": 2076.804375, "audio_path": "audio/native/M_EN_030.flac"}
+{"media_id": "M_EN_031", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 2282.325375, "audio_path": "audio/native/M_EN_031.flac"}
+{"media_id": "M_EN_032", "genre": "discussion", "topic": "health", "language": "en", "duration_sec": 2041.452, "audio_path": "audio/native/M_EN_032.flac"}
+{"media_id": "M_EN_033", "genre": "commentary", "topic": "arts", "language": "en", "duration_sec": 2344.693, "audio_path": "audio/native/M_EN_033.flac"}
+{"media_id": "M_EN_034", "genre": "vlog", "topic": "entertainment", "language": "en", "duration_sec": 2200.832, "audio_path": "audio/native/M_EN_034.flac"}
+{"media_id": "M_EN_035", "genre": "drama_variety", "topic": "entertainment", "language": "en", "duration_sec": 1836.535875, "audio_path": "audio/native/M_EN_035.flac"}
+{"media_id": "M_EN_036", "genre": "vlog", "topic": "lifestyle", "language": "en", "duration_sec": 2185.044188, "audio_path": "audio/native/M_EN_036.flac"}
+{"media_id": "M_EN_037", "genre": "discussion", "topic": "sports", "language": "en", "duration_sec": 2051.274063, "audio_path": "audio/native/M_EN_037.flac"}
+{"media_id": "M_EN_038", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 3223.701375, "audio_path": "audio/native/M_EN_038.flac"}
+{"media_id": "M_EN_039", "genre": "lecture", "topic": "business", "language": "en", "duration_sec": 3274.826313, "audio_path": "audio/native/M_EN_039.flac"}
+{"media_id": "M_EN_040", "genre": "lecture", "topic": "education", "language": "en", "duration_sec": 2842.819063, "audio_path": "audio/native/M_EN_040.flac"}
+{"media_id": "M_EN_041", "genre": "lecture", "topic": "health", "language": "en", "duration_sec": 2624.029063, "audio_path": "audio/native/M_EN_041.flac"}
+{"media_id": "M_EN_042", "genre": "lecture", "topic": "education", "language": "en", "duration_sec": 2196.096, "audio_path": "audio/native/M_EN_042.flac"}
+{"media_id": "M_EN_043", "genre": "lecture", "topic": "health", "language": "en", "duration_sec": 1960.896, "audio_path": "audio/native/M_EN_043.flac"}
+{"media_id": "M_EN_044", "genre": "commentary", "topic": "lifestyle", "language": "en", "duration_sec": 2044.807313, "audio_path": "audio/native/M_EN_044.flac"}
+{"media_id": "M_EN_045", "genre": "documentary", "topic": "education", "language": "en", "duration_sec": 2319.789625, "audio_path": "audio/native/M_EN_045.flac"}
+{"media_id": "M_EN_046", "genre": "commentary", "topic": "lifestyle", "language": "en", "duration_sec": 1881.872875, "audio_path": "audio/native/M_EN_046.flac"}
+{"media_id": "M_EN_047", "genre": "lecture", "topic": "health", "language": "en", "duration_sec": 2466.504875, "audio_path": "audio/native/M_EN_047.flac"}
+{"media_id": "M_EN_048", "genre": "discussion", "topic": "business", "language": "en", "duration_sec": 2013.170125, "audio_path": "audio/native/M_EN_048.flac"}
+{"media_id": "M_EN_049", "genre": "discussion", "topic": "health", "language": "en", "duration_sec": 2391.445375, "audio_path": "audio/native/M_EN_049.flac"}
+{"media_id": "M_EN_050", "genre": "vlog", "topic": "lifestyle", "language": "en", "duration_sec": 1983.253375, "audio_path": "audio/native/M_EN_050.flac"}
+{"media_id": "M_EN_051", "genre": "lecture", "topic": "technology", "language": "en", "duration_sec": 3579.866875, "audio_path": "audio/native/M_EN_051.flac"}
+{"media_id": "M_EN_052", "genre": "commentary", "topic": "lifestyle", "language": "en", "duration_sec": 2155.578063, "audio_path": "audio/native/M_EN_052.flac"}
+{"media_id": "M_EN_053", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 3132.058438, "audio_path": "audio/native/M_EN_053.flac"}
+{"media_id": "M_EN_054", "genre": "lecture", "topic": "business", "language": "en", "duration_sec": 2141.9015, "audio_path": "audio/native/M_EN_054.flac"}
+{"media_id": "M_EN_055", "genre": "documentary", "topic": "education", "language": "en", "duration_sec": 2991.194563, "audio_path": "audio/native/M_EN_055.flac"}
+{"media_id": "M_EN_056", "genre": "discussion", "topic": "arts", "language": "en", "duration_sec": 2251.178688, "audio_path": "audio/native/M_EN_056.flac"}
+{"media_id": "M_EN_057", "genre": "drama_variety", "topic": "arts", "language": "en", "duration_sec": 3421.495188, "audio_path": "audio/native/M_EN_057.flac"}
+{"media_id": "M_EN_058", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 3396.352, "audio_path": "audio/native/M_EN_058.flac"}
+{"media_id": "M_EN_059", "genre": "discussion", "topic": "arts", "language": "en", "duration_sec": 3453.469063, "audio_path": "audio/native/M_EN_059.flac"}
+{"media_id": "M_EN_060", "genre": "discussion", "topic": "business", "language": "en", "duration_sec": 2181.282563, "audio_path": "audio/native/M_EN_060.flac"}
+{"media_id": "M_ZH_001", "genre": "documentary", "topic": "lifestyle", "language": "zh", "duration_sec": 2178.542625, "audio_path": "audio/native/M_ZH_001.flac"}
+{"media_id": "M_ZH_002", "genre": "live_stream", "topic": "sports", "language": "zh", "duration_sec": 3353.173375, "audio_path": "audio/native/M_ZH_002.flac"}
+{"media_id": "M_ZH_003", "genre": "live_stream", "topic": "lifestyle", "language": "zh", "duration_sec": 3454.548813, "audio_path": "audio/native/M_ZH_003.flac"}
+{"media_id": "M_ZH_004", "genre": "live_stream", "topic": "business", "language": "zh", "duration_sec": 2739.049125, "audio_path": "audio/native/M_ZH_004.flac"}
+{"media_id": "M_ZH_005", "genre": "live_stream", "topic": "gaming", "language": "zh", "duration_sec": 2914.777688, "audio_path": "audio/native/M_ZH_005.flac"}
+{"media_id": "M_ZH_006", "genre": "lecture", "topic": "technology", "language": "zh", "duration_sec": 2259.046188, "audio_path": "audio/native/M_ZH_006.flac"}
+{"media_id": "M_ZH_007", "genre": "lecture", "topic": "business", "language": "zh", "duration_sec": 2937.997688, "audio_path": "audio/native/M_ZH_007.flac"}
+{"media_id": "M_ZH_008", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 2690.194313, "audio_path": "audio/native/M_ZH_008.flac"}
+{"media_id": "M_ZH_009", "genre": "documentary", "topic": "education", "language": "zh", "duration_sec": 2052.516313, "audio_path": "audio/native/M_ZH_009.flac"}
+{"media_id": "M_ZH_010", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 1925.48, "audio_path": "audio/native/M_ZH_010.flac"}
+{"media_id": "M_ZH_011", "genre": "live_stream", "topic": "arts", "language": "zh", "duration_sec": 1980.104875, "audio_path": "audio/native/M_ZH_011.flac"}
+{"media_id": "M_ZH_012", "genre": "documentary", "topic": "education", "language": "zh", "duration_sec": 3166.470438, "audio_path": "audio/native/M_ZH_012.flac"}
+{"media_id": "M_ZH_013", "genre": "drama_variety", "topic": "lifestyle", "language": "zh", "duration_sec": 2551.9195, "audio_path": "audio/native/M_ZH_013.flac"}
+{"media_id": "M_ZH_014", "genre": "documentary", "topic": "education", "language": "zh", "duration_sec": 1841.386688, "audio_path": "audio/native/M_ZH_014.flac"}
+{"media_id": "M_ZH_015", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 2729.633438, "audio_path": "audio/native/M_ZH_015.flac"}
+{"media_id": "M_ZH_016", "genre": "discussion", "topic": "sports", "language": "zh", "duration_sec": 2257.444, "audio_path": "audio/native/M_ZH_016.flac"}
+{"media_id": "M_ZH_017", "genre": "lecture", "topic": "technology", "language": "zh", "duration_sec": 2068.735438, "audio_path": "audio/native/M_ZH_017.flac"}
+{"media_id": "M_ZH_018", "genre": "discussion", "topic": "health", "language": "zh", "duration_sec": 2860.025063, "audio_path": "audio/native/M_ZH_018.flac"}
+{"media_id": "M_ZH_019", "genre": "commentary", "topic": "business", "language": "zh", "duration_sec": 2294.016, "audio_path": "audio/native/M_ZH_019.flac"}
+{"media_id": "M_ZH_020", "genre": "lecture", "topic": "sports", "language": "zh", "duration_sec": 2022.21425, "audio_path": "audio/native/M_ZH_020.flac"}
+{"media_id": "M_ZH_021", "genre": "live_stream", "topic": "business", "language": "zh", "duration_sec": 3299.72975, "audio_path": "audio/native/M_ZH_021.flac"}
+{"media_id": "M_ZH_022", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 2094.138063, "audio_path": "audio/native/M_ZH_022.flac"}
+{"media_id": "M_ZH_023", "genre": "discussion", "topic": "technology", "language": "zh", "duration_sec": 2891.139813, "audio_path": "audio/native/M_ZH_023.flac"}
+{"media_id": "M_ZH_024", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 2940.981438, "audio_path": "audio/native/M_ZH_024.flac"}
+{"media_id": "M_ZH_025", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 3472.381688, "audio_path": "audio/native/M_ZH_025.flac"}
+{"media_id": "M_ZH_026", "genre": "discussion", "topic": "sports", "language": "zh", "duration_sec": 2870.114125, "audio_path": "audio/native/M_ZH_026.flac"}
+{"media_id": "M_ZH_027", "genre": "discussion", "topic": "health", "language": "zh", "duration_sec": 2085.802125, "audio_path": "audio/native/M_ZH_027.flac"}
+{"media_id": "M_ZH_028", "genre": "live_stream", "topic": "gaming", "language": "zh", "duration_sec": 1882.17475, "audio_path": "audio/native/M_ZH_028.flac"}
+{"media_id": "M_ZH_029", "genre": "discussion", "topic": "business", "language": "zh", "duration_sec": 2696.810688, "audio_path": "audio/native/M_ZH_029.flac"}
+{"media_id": "M_ZH_030", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 2506.24, "audio_path": "audio/native/M_ZH_030.flac"}
+{"media_id": "M_ZH_031", "genre": "live_stream", "topic": "gaming", "language": "zh", "duration_sec": 3468.469125, "audio_path": "audio/native/M_ZH_031.flac"}
+{"media_id": "M_ZH_032", "genre": "drama_variety", "topic": "health", "language": "zh", "duration_sec": 2725.012625, "audio_path": "audio/native/M_ZH_032.flac"}
+{"media_id": "M_ZH_033", "genre": "drama_variety", "topic": "arts", "language": "zh", "duration_sec": 2695.442, "audio_path": "audio/native/M_ZH_033.flac"}
+{"media_id": "M_ZH_034", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 1852.395125, "audio_path": "audio/native/M_ZH_034.flac"}
+{"media_id": "M_ZH_035", "genre": "documentary", "topic": "education", "language": "zh", "duration_sec": 2142.145313, "audio_path": "audio/native/M_ZH_035.flac"}
+{"media_id": "M_ZH_036", "genre": "live_stream", "topic": "gaming", "language": "zh", "duration_sec": 3040.235125, "audio_path": "audio/native/M_ZH_036.flac"}
+{"media_id": "M_ZH_037", "genre": "live_stream", "topic": "gaming", "language": "zh", "duration_sec": 2175.849125, "audio_path": "audio/native/M_ZH_037.flac"}
+{"media_id": "M_ZH_038", "genre": "lecture", "topic": "sports", "language": "zh", "duration_sec": 3529.084813, "audio_path": "audio/native/M_ZH_038.flac"}
+{"media_id": "M_ZH_039", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 1886.226625, "audio_path": "audio/native/M_ZH_039.flac"}
+{"media_id": "M_ZH_040", "genre": "drama_variety", "topic": "lifestyle", "language": "zh", "duration_sec": 2731.99025, "audio_path": "audio/native/M_ZH_040.flac"}
+{"media_id": "M_ZH_041", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 2448.5675, "audio_path": "audio/native/M_ZH_041.flac"}
+{"media_id": "M_ZH_042", "genre": "drama_variety", "topic": "lifestyle", "language": "zh", "duration_sec": 2489.829313, "audio_path": "audio/native/M_ZH_042.flac"}
+{"media_id": "M_ZH_043", "genre": "discussion", "topic": "arts", "language": "zh", "duration_sec": 2236.64, "audio_path": "audio/native/M_ZH_043.flac"}
+{"media_id": "M_ZH_044", "genre": "lecture", "topic": "health", "language": "zh", "duration_sec": 3041.767625, "audio_path": "audio/native/M_ZH_044.flac"}
+{"media_id": "M_ZH_045", "genre": "documentary", "topic": "business", "language": "zh", "duration_sec": 3000.180688, "audio_path": "audio/native/M_ZH_045.flac"}
+{"media_id": "M_ZH_046", "genre": "documentary", "topic": "education", "language": "zh", "duration_sec": 2470.405813, "audio_path": "audio/native/M_ZH_046.flac"}
+{"media_id": "M_ZH_047", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 1832.008, "audio_path": "audio/native/M_ZH_047.flac"}
+{"media_id": "M_ZH_048", "genre": "commentary", "topic": "arts", "language": "zh", "duration_sec": 1811.261, "audio_path": "audio/native/M_ZH_048.flac"}
+{"media_id": "M_ZH_049", "genre": "live_stream", "topic": "gaming", "language": "zh", "duration_sec": 2031.08, "audio_path": "audio/native/M_ZH_049.flac"}
+{"media_id": "M_ZH_050", "genre": "vlog", "topic": "business", "language": "zh", "duration_sec": 1863.076313, "audio_path": "audio/native/M_ZH_050.flac"}
+{"media_id": "M_ZH_051", "genre": "lecture", "topic": "education", "language": "zh", "duration_sec": 3232.27575, "audio_path": "audio/native/M_ZH_051.flac"}
+{"media_id": "M_ZH_052", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 2082.214625, "audio_path": "audio/native/M_ZH_052.flac"}
+{"media_id": "M_ZH_053", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 2783.68, "audio_path": "audio/native/M_ZH_053.flac"}
+{"media_id": "M_ZH_054", "genre": "lecture", "topic": "business", "language": "zh", "duration_sec": 3527.563938, "audio_path": "audio/native/M_ZH_054.flac"}
+{"media_id": "M_ZH_055", "genre": "documentary", "topic": "education", "language": "zh", "duration_sec": 1984.609563, "audio_path": "audio/native/M_ZH_055.flac"}
+{"media_id": "M_ZH_056", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 2730.004938, "audio_path": "audio/native/M_ZH_056.flac"}
+{"media_id": "M_ZH_057", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 2906.12, "audio_path": "audio/native/M_ZH_057.flac"}
+{"media_id": "M_ZH_058", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 2768.16, "audio_path": "audio/native/M_ZH_058.flac"}
+{"media_id": "M_ZH_059", "genre": "discussion", "topic": "technology", "language": "zh", "duration_sec": 2384.039188, "audio_path": "audio/native/M_ZH_059.flac"}
+{"media_id": "M_ZH_060", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 2981.372563, "audio_path": "audio/native/M_ZH_060.flac"}

metadata/media/native/S.jsonl

@@ -0,0 +1,120 @@
+{"media_id": "S_EN_001", "genre": "lecture", "topic": "technology", "language": "en", "duration_sec": 684.373375, "audio_path": "audio/native/S_EN_001.flac"}
+{"media_id": "S_EN_002", "genre": "commentary", "topic": "sports", "language": "en", "duration_sec": 941.25575, "audio_path": "audio/native/S_EN_002.flac"}
+{"media_id": "S_EN_003", "genre": "lecture", "topic": "arts", "language": "en", "duration_sec": 749.400875, "audio_path": "audio/native/S_EN_003.flac"}
+{"media_id": "S_EN_004", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 734.447188, "audio_path": "audio/native/S_EN_004.flac"}
+{"media_id": "S_EN_005", "genre": "discussion", "topic": "business", "language": "en", "duration_sec": 626.962, "audio_path": "audio/native/S_EN_005.flac"}
+{"media_id": "S_EN_006", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 1058.655813, "audio_path": "audio/native/S_EN_006.flac"}
+{"media_id": "S_EN_007", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 616.211188, "audio_path": "audio/native/S_EN_007.flac"}
+{"media_id": "S_EN_008", "genre": "lecture", "topic": "education", "language": "en", "duration_sec": 1728.15675, "audio_path": "audio/native/S_EN_008.flac"}
+{"media_id": "S_EN_009", "genre": "vlog", "topic": "lifestyle", "language": "en", "duration_sec": 728.468063, "audio_path": "audio/native/S_EN_009.flac"}
+{"media_id": "S_EN_010", "genre": "discussion", "topic": "health", "language": "en", "duration_sec": 1178.877125, "audio_path": "audio/native/S_EN_010.flac"}
+{"media_id": "S_EN_011", "genre": "drama_variety", "topic": "entertainment", "language": "en", "duration_sec": 659.072, "audio_path": "audio/native/S_EN_011.flac"}
+{"media_id": "S_EN_012", "genre": "commentary", "topic": "sports", "language": "en", "duration_sec": 600.170688, "audio_path": "audio/native/S_EN_012.flac"}
+{"media_id": "S_EN_013", "genre": "live_stream", "topic": "sports", "language": "en", "duration_sec": 768.905625, "audio_path": "audio/native/S_EN_013.flac"}
+{"media_id": "S_EN_014", "genre": "vlog", "topic": "business", "language": "en", "duration_sec": 877.12, "audio_path": "audio/native/S_EN_014.flac"}
+{"media_id": "S_EN_015", "genre": "lecture", "topic": "business", "language": "en", "duration_sec": 651.79575, "audio_path": "audio/native/S_EN_015.flac"}
+{"media_id": "S_EN_016", "genre": "vlog", "topic": "lifestyle", "language": "en", "duration_sec": 1093.636688, "audio_path": "audio/native/S_EN_016.flac"}
+{"media_id": "S_EN_017", "genre": "lecture", "topic": "technology", "language": "en", "duration_sec": 984.944063, "audio_path": "audio/native/S_EN_017.flac"}
+{"media_id": "S_EN_018", "genre": "lecture", "topic": "technology", "language": "en", "duration_sec": 1046.082188, "audio_path": "audio/native/S_EN_018.flac"}
+{"media_id": "S_EN_019", "genre": "documentary", "topic": "technology", "language": "en", "duration_sec": 700.117375, "audio_path": "audio/native/S_EN_019.flac"}
+{"media_id": "S_EN_020", "genre": "lecture", "topic": "business", "language": "en", "duration_sec": 1236.578688, "audio_path": "audio/native/S_EN_020.flac"}
+{"media_id": "S_EN_021", "genre": "commentary", "topic": "arts", "language": "en", "duration_sec": 820.885375, "audio_path": "audio/native/S_EN_021.flac"}
+{"media_id": "S_EN_022", "genre": "commentary", "topic": "technology", "language": "en", "duration_sec": 1073.11025, "audio_path": "audio/native/S_EN_022.flac"}
+{"media_id": "S_EN_023", "genre": "documentary", "topic": "sports", "language": "en", "duration_sec": 1382.063313, "audio_path": "audio/native/S_EN_023.flac"}
+{"media_id": "S_EN_024", "genre": "documentary", "topic": "technology", "language": "en", "duration_sec": 686.528, "audio_path": "audio/native/S_EN_024.flac"}
+{"media_id": "S_EN_025", "genre": "commentary", "topic": "technology", "language": "en", "duration_sec": 753.963563, "audio_path": "audio/native/S_EN_025.flac"}
+{"media_id": "S_EN_026", "genre": "discussion", "topic": "sports", "language": "en", "duration_sec": 754.567313, "audio_path": "audio/native/S_EN_026.flac"}
+{"media_id": "S_EN_027", "genre": "commentary", "topic": "arts", "language": "en", "duration_sec": 1522.102875, "audio_path": "audio/native/S_EN_027.flac"}
+{"media_id": "S_EN_028", "genre": "discussion", "topic": "business", "language": "en", "duration_sec": 826.375, "audio_path": "audio/native/S_EN_028.flac"}
+{"media_id": "S_EN_029", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 862.50525, "audio_path": "audio/native/S_EN_029.flac"}
+{"media_id": "S_EN_030", "genre": "commentary", "topic": "technology", "language": "en", "duration_sec": 810.956938, "audio_path": "audio/native/S_EN_030.flac"}
+{"media_id": "S_EN_031", "genre": "commentary", "topic": "health", "language": "en", "duration_sec": 684.09475, "audio_path": "audio/native/S_EN_031.flac"}
+{"media_id": "S_EN_032", "genre": "commentary", "topic": "sports", "language": "en", "duration_sec": 881.237375, "audio_path": "audio/native/S_EN_032.flac"}
+{"media_id": "S_EN_033", "genre": "discussion", "topic": "sports", "language": "en", "duration_sec": 1237.008313, "audio_path": "audio/native/S_EN_033.flac"}
+{"media_id": "S_EN_034", "genre": "discussion", "topic": "education", "language": "en", "duration_sec": 1280.81275, "audio_path": "audio/native/S_EN_034.flac"}
+{"media_id": "S_EN_035", "genre": "drama_variety", "topic": "entertainment", "language": "en", "duration_sec": 909.525375, "audio_path": "audio/native/S_EN_035.flac"}
+{"media_id": "S_EN_036", "genre": "commentary", "topic": "arts", "language": "en", "duration_sec": 608.583438, "audio_path": "audio/native/S_EN_036.flac"}
+{"media_id": "S_EN_037", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 1189.093938, "audio_path": "audio/native/S_EN_037.flac"}
+{"media_id": "S_EN_038", "genre": "lecture", "topic": "technology", "language": "en", "duration_sec": 627.240688, "audio_path": "audio/native/S_EN_038.flac"}
+{"media_id": "S_EN_039", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 1766.005313, "audio_path": "audio/native/S_EN_039.flac"}
+{"media_id": "S_EN_040", "genre": "vlog", "topic": "lifestyle", "language": "en", "duration_sec": 1529.602938, "audio_path": "audio/native/S_EN_040.flac"}
+{"media_id": "S_EN_041", "genre": "vlog", "topic": "lifestyle", "language": "en", "duration_sec": 1716.953125, "audio_path": "audio/native/S_EN_041.flac"}
+{"media_id": "S_EN_042", "genre": "documentary", "topic": "entertainment", "language": "en", "duration_sec": 600.096563, "audio_path": "audio/native/S_EN_042.flac"}
+{"media_id": "S_EN_043", "genre": "vlog", "topic": "lifestyle", "language": "en", "duration_sec": 1743.7025, "audio_path": "audio/native/S_EN_043.flac"}
+{"media_id": "S_EN_044", "genre": "vlog", "topic": "lifestyle", "language": "en", "duration_sec": 856.955688, "audio_path": "audio/native/S_EN_044.flac"}
+{"media_id": "S_EN_045", "genre": "discussion", "topic": "health", "language": "en", "duration_sec": 1450.922125, "audio_path": "audio/native/S_EN_045.flac"}
+{"media_id": "S_EN_046", "genre": "drama_variety", "topic": "entertainment", "language": "en", "duration_sec": 882.811125, "audio_path": "audio/native/S_EN_046.flac"}
+{"media_id": "S_EN_047", "genre": "commentary", "topic": "gaming", "language": "en", "duration_sec": 667.991688, "audio_path": "audio/native/S_EN_047.flac"}
+{"media_id": "S_EN_048", "genre": "lecture", "topic": "health", "language": "en", "duration_sec": 899.343688, "audio_path": "audio/native/S_EN_048.flac"}
+{"media_id": "S_EN_049", "genre": "drama_variety", "topic": "entertainment", "language": "en", "duration_sec": 911.552, "audio_path": "audio/native/S_EN_049.flac"}
+{"media_id": "S_EN_050", "genre": "discussion", "topic": "technology", "language": "en", "duration_sec": 923.864, "audio_path": "audio/native/S_EN_050.flac"}
+{"media_id": "S_EN_051", "genre": "discussion", "topic": "business", "language": "en", "duration_sec": 1114.395313, "audio_path": "audio/native/S_EN_051.flac"}
+{"media_id": "S_EN_052", "genre": "commentary", "topic": "sports", "language": "en", "duration_sec": 630.503063, "audio_path": "audio/native/S_EN_052.flac"}
+{"media_id": "S_EN_053", "genre": "documentary", "topic": "business", "language": "en", "duration_sec": 653.247, "audio_path": "audio/native/S_EN_053.flac"}
+{"media_id": "S_EN_054", "genre": "discussion", "topic": "health", "language": "en", "duration_sec": 665.67075, "audio_path": "audio/native/S_EN_054.flac"}
+{"media_id": "S_EN_055", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 682.14425, "audio_path": "audio/native/S_EN_055.flac"}
+{"media_id": "S_EN_056", "genre": "documentary", "topic": "education", "language": "en", "duration_sec": 600.32875, "audio_path": "audio/native/S_EN_056.flac"}
+{"media_id": "S_EN_057", "genre": "vlog", "topic": "lifestyle", "language": "en", "duration_sec": 1004.117375, "audio_path": "audio/native/S_EN_057.flac"}
+{"media_id": "S_EN_058", "genre": "discussion", "topic": "health", "language": "en", "duration_sec": 1214.549375, "audio_path": "audio/native/S_EN_058.flac"}
+{"media_id": "S_EN_059", "genre": "live_stream", "topic": "gaming", "language": "en", "duration_sec": 765.845375, "audio_path": "audio/native/S_EN_059.flac"}
+{"media_id": "S_EN_060", "genre": "documentary", "topic": "business", "language": "en", "duration_sec": 674.841563, "audio_path": "audio/native/S_EN_060.flac"}
+{"media_id": "S_ZH_001", "genre": "live_stream", "topic": "gaming", "language": "zh", "duration_sec": 879.548688, "audio_path": "audio/native/S_ZH_001.flac"}
+{"media_id": "S_ZH_002", "genre": "lecture", "topic": "education", "language": "zh", "duration_sec": 1375.422438, "audio_path": "audio/native/S_ZH_002.flac"}
+{"media_id": "S_ZH_003", "genre": "documentary", "topic": "education", "language": "zh", "duration_sec": 759.780188, "audio_path": "audio/native/S_ZH_003.flac"}
+{"media_id": "S_ZH_004", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 611.811, "audio_path": "audio/native/S_ZH_004.flac"}
+{"media_id": "S_ZH_005", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 857.408, "audio_path": "audio/native/S_ZH_005.flac"}
+{"media_id": "S_ZH_006", "genre": "lecture", "topic": "health", "language": "zh", "duration_sec": 1299.434688, "audio_path": "audio/native/S_ZH_006.flac"}
+{"media_id": "S_ZH_007", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 1288.7075, "audio_path": "audio/native/S_ZH_007.flac"}
+{"media_id": "S_ZH_008", "genre": "live_stream", "topic": "gaming", "language": "zh", "duration_sec": 1310.580688, "audio_path": "audio/native/S_ZH_008.flac"}
+{"media_id": "S_ZH_009", "genre": "discussion", "topic": "education", "language": "zh", "duration_sec": 1682.192875, "audio_path": "audio/native/S_ZH_009.flac"}
+{"media_id": "S_ZH_010", "genre": "commentary", "topic": "entertainment", "language": "zh", "duration_sec": 601.443313, "audio_path": "audio/native/S_ZH_010.flac"}
+{"media_id": "S_ZH_011", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 623.966625, "audio_path": "audio/native/S_ZH_011.flac"}
+{"media_id": "S_ZH_012", "genre": "documentary", "topic": "technology", "language": "zh", "duration_sec": 1780.065, "audio_path": "audio/native/S_ZH_012.flac"}
+{"media_id": "S_ZH_013", "genre": "discussion", "topic": "lifestyle", "language": "zh", "duration_sec": 1007.786688, "audio_path": "audio/native/S_ZH_013.flac"}
+{"media_id": "S_ZH_014", "genre": "lecture", "topic": "arts", "language": "zh", "duration_sec": 611.2305, "audio_path": "audio/native/S_ZH_014.flac"}
+{"media_id": "S_ZH_015", "genre": "documentary", "topic": "education", "language": "zh", "duration_sec": 916.60775, "audio_path": "audio/native/S_ZH_015.flac"}
+{"media_id": "S_ZH_016", "genre": "discussion", "topic": "lifestyle", "language": "zh", "duration_sec": 670.53425, "audio_path": "audio/native/S_ZH_016.flac"}
+{"media_id": "S_ZH_017", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 991.968125, "audio_path": "audio/native/S_ZH_017.flac"}
+{"media_id": "S_ZH_018", "genre": "drama_variety", "topic": "lifestyle", "language": "zh", "duration_sec": 1703.125625, "audio_path": "audio/native/S_ZH_018.flac"}
+{"media_id": "S_ZH_019", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 1501.76, "audio_path": "audio/native/S_ZH_019.flac"}
+{"media_id": "S_ZH_020", "genre": "vlog", "topic": "sports", "language": "zh", "duration_sec": 819.060688, "audio_path": "audio/native/S_ZH_020.flac"}
+{"media_id": "S_ZH_021", "genre": "vlog", "topic": "gaming", "language": "zh", "duration_sec": 713.88, "audio_path": "audio/native/S_ZH_021.flac"}
+{"media_id": "S_ZH_022", "genre": "commentary", "topic": "technology", "language": "zh", "duration_sec": 606.249813, "audio_path": "audio/native/S_ZH_022.flac"}
+{"media_id": "S_ZH_023", "genre": "discussion", "topic": "gaming", "language": "zh", "duration_sec": 1506.139188, "audio_path": "audio/native/S_ZH_023.flac"}
+{"media_id": "S_ZH_024", "genre": "lecture", "topic": "education", "language": "zh", "duration_sec": 624.732938, "audio_path": "audio/native/S_ZH_024.flac"}
+{"media_id": "S_ZH_025", "genre": "live_stream", "topic": "gaming", "language": "zh", "duration_sec": 699.733375, "audio_path": "audio/native/S_ZH_025.flac"}
+{"media_id": "S_ZH_026", "genre": "lecture", "topic": "technology", "language": "zh", "duration_sec": 841.472063, "audio_path": "audio/native/S_ZH_026.flac"}
+{"media_id": "S_ZH_027", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 1291.075938, "audio_path": "audio/native/S_ZH_027.flac"}
+{"media_id": "S_ZH_028", "genre": "live_stream", "topic": "gaming", "language": "zh", "duration_sec": 863.201875, "audio_path": "audio/native/S_ZH_028.flac"}
+{"media_id": "S_ZH_029", "genre": "lecture", "topic": "business", "language": "zh", "duration_sec": 1104.3875, "audio_path": "audio/native/S_ZH_029.flac"}
+{"media_id": "S_ZH_030", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 767.829375, "audio_path": "audio/native/S_ZH_030.flac"}
+{"media_id": "S_ZH_031", "genre": "discussion", "topic": "lifestyle", "language": "zh", "duration_sec": 1187.433688, "audio_path": "audio/native/S_ZH_031.flac"}
+{"media_id": "S_ZH_032", "genre": "live_stream", "topic": "gaming", "language": "zh", "duration_sec": 1044.178188, "audio_path": "audio/native/S_ZH_032.flac"}
+{"media_id": "S_ZH_033", "genre": "discussion", "topic": "lifestyle", "language": "zh", "duration_sec": 1325.511125, "audio_path": "audio/native/S_ZH_033.flac"}
+{"media_id": "S_ZH_034", "genre": "commentary", "topic": "entertainment", "language": "zh", "duration_sec": 838.310063, "audio_path": "audio/native/S_ZH_034.flac"}
+{"media_id": "S_ZH_035", "genre": "commentary", "topic": "sports", "language": "zh", "duration_sec": 607.259875, "audio_path": "audio/native/S_ZH_035.flac"}
+{"media_id": "S_ZH_036", "genre": "live_stream", "topic": "gaming", "language": "zh", "duration_sec": 784.404938, "audio_path": "audio/native/S_ZH_036.flac"}
+{"media_id": "S_ZH_037", "genre": "documentary", "topic": "education", "language": "zh", "duration_sec": 737.001375, "audio_path": "audio/native/S_ZH_037.flac"}
+{"media_id": "S_ZH_038", "genre": "documentary", "topic": "education", "language": "zh", "duration_sec": 1554.410688, "audio_path": "audio/native/S_ZH_038.flac"}
+{"media_id": "S_ZH_039", "genre": "drama_variety", "topic": "lifestyle", "language": "zh", "duration_sec": 1710.68, "audio_path": "audio/native/S_ZH_039.flac"}
+{"media_id": "S_ZH_040", "genre": "lecture", "topic": "sports", "language": "zh", "duration_sec": 1044.433563, "audio_path": "audio/native/S_ZH_040.flac"}
+{"media_id": "S_ZH_041", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 1043.574438, "audio_path": "audio/native/S_ZH_041.flac"}
+{"media_id": "S_ZH_042", "genre": "discussion", "topic": "business", "language": "zh", "duration_sec": 1763.207313, "audio_path": "audio/native/S_ZH_042.flac"}
+{"media_id": "S_ZH_043", "genre": "discussion", "topic": "sports", "language": "zh", "duration_sec": 744.3505, "audio_path": "audio/native/S_ZH_043.flac"}
+{"media_id": "S_ZH_044", "genre": "discussion", "topic": "entertainment", "language": "zh", "duration_sec": 795.394625, "audio_path": "audio/native/S_ZH_044.flac"}
+{"media_id": "S_ZH_045", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 870.771563, "audio_path": "audio/native/S_ZH_045.flac"}
+{"media_id": "S_ZH_046", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 674.528125, "audio_path": "audio/native/S_ZH_046.flac"}
+{"media_id": "S_ZH_047", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 1005.563375, "audio_path": "audio/native/S_ZH_047.flac"}
+{"media_id": "S_ZH_048", "genre": "lecture", "topic": "arts", "language": "zh", "duration_sec": 1244.310938, "audio_path": "audio/native/S_ZH_048.flac"}
+{"media_id": "S_ZH_049", "genre": "commentary", "topic": "entertainment", "language": "zh", "duration_sec": 659.284188, "audio_path": "audio/native/S_ZH_049.flac"}
+{"media_id": "S_ZH_050", "genre": "live_stream", "topic": "entertainment", "language": "zh", "duration_sec": 1398.421813, "audio_path": "audio/native/S_ZH_050.flac"}
+{"media_id": "S_ZH_051", "genre": "discussion", "topic": "business", "language": "zh", "duration_sec": 1713.365625, "audio_path": "audio/native/S_ZH_051.flac"}
+{"media_id": "S_ZH_052", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 775.94125, "audio_path": "audio/native/S_ZH_052.flac"}
+{"media_id": "S_ZH_053", "genre": "documentary", "topic": "education", "language": "zh", "duration_sec": 1714.468625, "audio_path": "audio/native/S_ZH_053.flac"}
+{"media_id": "S_ZH_054", "genre": "commentary", "topic": "sports", "language": "zh", "duration_sec": 809.24, "audio_path": "audio/native/S_ZH_054.flac"}
+{"media_id": "S_ZH_055", "genre": "discussion", "topic": "business", "language": "zh", "duration_sec": 1703.488, "audio_path": "audio/native/S_ZH_055.flac"}
+{"media_id": "S_ZH_056", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 609.361313, "audio_path": "audio/native/S_ZH_056.flac"}
+{"media_id": "S_ZH_057", "genre": "drama_variety", "topic": "arts", "language": "zh", "duration_sec": 637.085938, "audio_path": "audio/native/S_ZH_057.flac"}
+{"media_id": "S_ZH_058", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 848.317875, "audio_path": "audio/native/S_ZH_058.flac"}
+{"media_id": "S_ZH_059", "genre": "vlog", "topic": "lifestyle", "language": "zh", "duration_sec": 868.757375, "audio_path": "audio/native/S_ZH_059.flac"}
+{"media_id": "S_ZH_060", "genre": "drama_variety", "topic": "entertainment", "language": "zh", "duration_sec": 663.92, "audio_path": "audio/native/S_ZH_060.flac"}

prepare/prepare_anchor.py

@@ -0,0 +1,369 @@
+#!/usr/bin/env python3
+"""Rebuild anchor (edited) audio from native audio + replay manifest.
+
+Reproduces, for each record in ``anchor_manifest.jsonl``, the edit that
+produced the anchor recording from its native source:
+
+  addition      overlay sound events at SNR-calibrated volume
+  deletion      hard silence or blurred masking of regions
+  modification  region-scoped volume or speed change
+
+Only ``ffmpeg``/``ffprobe`` are required. Replay is exact except for
+blur_mask, whose rendering params were randomized in the original pipeline
+and are replaced with fixed defaults (the masked regions stay exact, which
+is what the questions depend on).
+
+Usage:
+    python prepare_anchor.py [--manifest metadata/media/anchor/anchor_manifest.jsonl]
+                             [--root .] [--only OPERATION] [--overwrite] [--dry-run]
+"""
+
+import argparse
+import json
+import math
+import os
+import re
+import shutil
+import subprocess
+import sys
+import tempfile
+from pathlib import Path
+
+def ffprobe_format(path: Path) -> tuple[int, int]:
+    """Return (sample_rate, channels) of the first audio stream."""
+    proc = subprocess.run(
+        ["ffprobe", "-v", "error", "-select_streams", "a:0",
+         "-show_entries", "stream=sample_rate,channels",
+         "-of", "csv=p=0", str(path)],
+        stdout=subprocess.PIPE, stderr=subprocess.PIPE,
+    )
+    rate, ch = proc.stdout.decode().strip().split(",")
+    return int(rate), int(ch)
+
+
+def read_jsonl(path: Path) -> list[dict]:
+    with open(path, encoding="utf-8") as fh:
+        return [json.loads(line) for line in fh if line.strip()]
+
+
+def run(cmd: list[str], dry_run: bool = False) -> None:
+    if dry_run:
+        print("    [dry-run] " + " ".join(cmd[:8]) + " ...")
+        return
+    proc = subprocess.run(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    if proc.returncode != 0:
+        err = proc.stderr.decode("utf-8", errors="replace").strip()
+        raise RuntimeError(f"command failed (rc={proc.returncode}): {' '.join(cmd[:6])}...\n{err[-800:]}")
+
+
+def ffprobe_duration(path: Path) -> float:
+    proc = subprocess.run(
+        ["ffprobe", "-v", "error", "-show_entries", "format=duration",
+         "-of", "default=noprint_wrappers=1:nokey=1", str(path)],
+        stdout=subprocess.PIPE, stderr=subprocess.PIPE,
+    )
+    return float(proc.stdout.decode().strip())
+
+
+def analyze_rms_db(path: Path, start: float | None = None, dur: float | None = None) -> float:
+    """Return RMS loudness (dB) of a file or a region of it."""
+    cmd = ["ffmpeg", "-hide_banner", "-loglevel", "info"]
+    if start is not None:
+        cmd += ["-ss", f"{start}"]
+    if dur is not None:
+        cmd += ["-t", f"{dur}"]
+    cmd += ["-i", str(path), "-af", "volumedetect", "-f", "null", "-"]
+    proc = subprocess.run(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    text = proc.stderr.decode("utf-8", errors="replace")
+    m = re.search(r"mean_volume: ([-\d.]+) dB", text)
+    return float(m.group(1)) if m else -30.0
+
+
+def out_codec_args(rate: int | None = None, channels: int | None = None) -> list[str]:
+    args = ["-c:a", "flac"]
+    if rate is not None:
+        args += ["-ar", str(rate)]
+    if channels is not None:
+        args += ["-ac", str(channels)]
+    return args
+
+
+def resolve_event(manifest_path: str, events_dir: Path) -> Path:
+    """Map a manifest event path to the local audio/events/ file."""
+    return events_dir / Path(manifest_path).name
+
+
+def replay_addition(rec: dict, native: Path, out: Path, events_dir: Path, dry_run: bool,
+                    fmt: tuple[int, int] | None = None) -> None:
+    positions = rec["params"]["positions"]
+    inputs = ["-i", str(native)]
+    filter_parts = []
+    mix_inputs = ["[0:a]"]
+
+    for idx, pos in enumerate(positions, start=1):
+        event_path = resolve_event(pos["event_audio_path"], events_dir)
+        if not event_path.is_file() and not dry_run:
+            raise FileNotFoundError(f"event audio missing: {event_path}")
+        inputs += ["-i", str(event_path)]
+
+        offset_ms = int(float(pos["position_sec"]) * 1000)
+        volume_db = pos.get("volume_db")
+        if volume_db is None:
+            snr = float(pos["snr_db"])
+            region_dur = float(pos.get("duration_sec") or 3.0)
+            bg_rms = analyze_rms_db(native, float(pos["position_sec"]), region_dur) if not dry_run else -25.0
+            ev_rms = analyze_rms_db(event_path) if not dry_run else -25.0
+            volume_db = round((bg_rms + snr) - ev_rms, 1)
+            volume_db = max(-30.0, min(30.0, volume_db))
+
+        label = f"evt{idx}"
+        filter_parts.append(f"[{idx}:a]adelay={offset_ms}|{offset_ms},volume={volume_db}dB[{label}]")
+        mix_inputs.append(f"[{label}]")
+
+    weights = " ".join(["1"] * len(mix_inputs))
+    filter_parts.append(
+        f"{''.join(mix_inputs)}amix=inputs={len(mix_inputs)}:duration=first"
+        f":dropout_transition=0:normalize=0:weights={weights}[mixed]"
+    )
+    rate, channels = fmt if fmt else (None, None)
+    cmd = ["ffmpeg", "-hide_banner", "-loglevel", "error", "-y", *inputs,
+           "-filter_complex", ";".join(filter_parts), "-map", "[mixed]",
+           *out_codec_args(rate, channels), str(out)]
+    run(cmd, dry_run)
+
+
+def replay_deletion(rec: dict, native: Path, out: Path, dry_run: bool) -> None:
+    mask_type = rec["params"].get("mask_type", "hard_mask")
+    regions = rec["params"]["regions"]
+
+    if mask_type == "hard_mask":
+        filters = [f"volume=enable='between(t,{s},{e})':volume=0" for s, e in regions]
+        cmd = ["ffmpeg", "-hide_banner", "-loglevel", "error", "-y", "-i", str(native),
+               "-af", ",".join(filters), *out_codec_args(), str(out)]
+        run(cmd, dry_run)
+        return
+
+    if mask_type == "blur_mask":
+        _replay_blur_mask(native, out, regions, dry_run)
+        return
+
+    raise ValueError(f"unsupported mask_type: {mask_type}")
+
+
+def _replay_blur_mask(native: Path, out: Path, regions: list, dry_run: bool) -> None:
+    """Deterministic blur mask (original used randomized params; regions are exact)."""
+    lowpass_freq = 300
+    blur_attenuation_db = -6.0
+    noise_level_db = -8.0
+    fade_sec = 0.5
+    noise_color = "pink"
+    dynamic_noise = True
+    fluct_db = 3.0
+    fluct_rate = 0.8
+
+    blur_gain = 10 ** (blur_attenuation_db / 20)
+    noise_gain = 10 ** (noise_level_db / 20)
+
+    if dynamic_noise:
+        lo = noise_gain * (10 ** (-fluct_db / 20))
+        hi = noise_gain * (10 ** (+fluct_db / 20))
+        rng = hi - lo
+        r1 = 2 * math.pi * fluct_rate
+        r2 = 2 * math.pi * (fluct_rate * 2.3)
+        noise_expr = f"{lo:.8f}+({rng:.8f})*(0.5+0.3*sin({r1}*t)+0.2*sin({r2}*t))"
+    else:
+        noise_expr = f"{noise_gain:.6f}"
+
+    valid = [(float(s), float(e)) for s, e in regions if float(e) > float(s)]
+    total_duration = ffprobe_duration(native) if not dry_run else 300.0
+
+    orig_parts, blur_parts = [], []
+    for s, e in valid:
+        seg_dur = e - s
+        eff_fade = min(fade_sec, seg_dur / 2.5)
+        fie, fos = s + eff_fade, e - eff_fade
+        orig_parts.append(
+            f"if(between(t,{s},{fie}),(({fie}-t)/{eff_fade:.4f}),"
+            f"if(between(t,{fie},{fos}),0,"
+            f"if(between(t,{fos},{e}),((t-{fos})/{eff_fade:.4f}),1)))"
+        )
+        blur_parts.append(
+            f"if(between(t,{s},{fie}),((t-{s})/{eff_fade:.4f}),"
+            f"if(between(t,{fie},{fos}),1,"
+            f"if(between(t,{fos},{e}),(({e}-t)/{eff_fade:.4f}),0)))"
+        )
+
+    if len(valid) == 1:
+        orig_env, blur_env = orig_parts[0], blur_parts[0]
+    else:
+        orig_env, blur_env = "1", "0"
+        for i in range(len(valid) - 1, -1, -1):
+            s, e = valid[i]
+            orig_env = f"if(between(t,{s},{e}),{orig_parts[i]},{orig_env})"
+            blur_env = f"if(between(t,{s},{e}),{blur_parts[i]},{blur_env})"
+
+    filter_complex = (
+        f"[0:a]asplit=2[orig][to_blur];"
+        f"[to_blur]lowpass=f={lowpass_freq},volume={blur_gain:.6f}[blurred];"
+        f"[1:a]volume='{noise_expr}':eval=frame[noise_scaled];"
+        f"[blurred][noise_scaled]amix=inputs=2:duration=first:weights=3 1[blur_noise];"
+        f"[orig]volume='{orig_env}':eval=frame[orig_env];"
+        f"[blur_noise]volume='{blur_env}':eval=frame[blur_env];"
+        f"[orig_env][blur_env]amix=inputs=2:duration=first:normalize=0[out]"
+    )
+    cmd = ["ffmpeg", "-hide_banner", "-loglevel", "error", "-y",
+           "-i", str(native),
+           "-f", "lavfi", "-i",
+           f"anoisesrc=color={noise_color}:duration={total_duration:.2f}:sample_rate=16000",
+           "-filter_complex", filter_complex, "-map", "[out]",
+           *out_codec_args(), str(out)]
+    run(cmd, dry_run)
+
+
+def _atempo_chain(factor: float) -> str:
+    parts = []
+    remaining = factor
+    while remaining > 2.0:
+        parts.append("atempo=2.0")
+        remaining /= 2.0
+    while remaining < 0.5:
+        parts.append("atempo=0.5")
+        remaining /= 0.5
+    parts.append(f"atempo={remaining:.4f}")
+    return ",".join(parts)
+
+
+def replay_modification(rec: dict, native: Path, out: Path, dry_run: bool) -> None:
+    kind = rec["params"]["kind"]
+    regions = rec["params"]["regions"]
+
+    if kind == "volume":
+        filters = []
+        for region in regions:
+            s, e = region["region_sec"]
+            gain = 10 ** (float(region["delta_db"]) / 20)
+            filters.append(f"volume=enable='between(t,{s},{e})':volume={gain}")
+        cmd = ["ffmpeg", "-hide_banner", "-loglevel", "error", "-y", "-i", str(native),
+               "-af", ",".join(filters), *out_codec_args(), str(out)]
+        run(cmd, dry_run)
+        return
+
+    if kind == "speed":
+        _replay_speed(native, out, regions, dry_run)
+        return
+
+    raise ValueError(f"unsupported modification kind: {kind}")
+
+
+def _replay_speed(native: Path, out: Path, regions: list, dry_run: bool) -> None:
+    """Apply region-scoped atempo and re-concatenate. Regions use original timeline."""
+    total = ffprobe_duration(native) if not dry_run else 600.0
+    segs = sorted(regions, key=lambda r: r["region_sec"][0])
+
+    # Build a clip plan: (kind, start, end, factor)
+    plan = []
+    cursor = 0.0
+    for region in segs:
+        s, e = region["region_sec"]
+        factor = float(region["speed_factor"])
+        if s > cursor + 0.05:
+            plan.append(("copy", cursor, s, None))
+        plan.append(("atempo", s, e, factor))
+        cursor = e
+    if cursor < total - 0.05:
+        plan.append(("copy", cursor, total, None))
+
+    if dry_run:
+        print(f"    [dry-run] speed modification: {len(plan)} clips")
+        return
+
+    tmpdir = tempfile.mkdtemp(prefix="anchor_speed_")
+    try:
+        clip_paths = []
+        for i, (kind, s, e, factor) in enumerate(plan):
+            seg_path = os.path.join(tmpdir, f"seg_{i:03d}.flac")
+            extract = ["ffmpeg", "-hide_banner", "-loglevel", "error", "-y",
+                       "-ss", f"{s}", "-to", f"{e}", "-i", str(native),
+                       *out_codec_args(), seg_path]
+            run(extract)
+            if kind == "atempo":
+                tempo_path = os.path.join(tmpdir, f"seg_{i:03d}_tempo.flac")
+                run(["ffmpeg", "-hide_banner", "-loglevel", "error", "-y",
+                     "-i", seg_path, "-af", _atempo_chain(factor),
+                     *out_codec_args(), tempo_path])
+                clip_paths.append(tempo_path)
+            else:
+                clip_paths.append(seg_path)
+
+        concat_list = os.path.join(tmpdir, "concat.txt")
+        with open(concat_list, "w", encoding="utf-8") as fh:
+            for p in clip_paths:
+                fh.write(f"file '{p}'\n")
+        run(["ffmpeg", "-hide_banner", "-loglevel", "error", "-y",
+             "-f", "concat", "-safe", "0", "-i", concat_list,
+             *out_codec_args(), str(out)])
+    finally:
+        shutil.rmtree(tmpdir, ignore_errors=True)
+
+
+def process_record(rec: dict, root: Path, overwrite: bool, dry_run: bool) -> str:
+    media_id = rec["media_id"]
+    operation = rec["operation"]
+    native = root / "audio" / "native" / Path(rec["native_audio_path"]).name
+    out = root / "audio" / "anchor" / Path(rec["target_audio_path"]).name
+    events_dir = root / "audio" / "events"
+
+    if out.is_file() and not overwrite and not dry_run:
+        return "skip"
+    if not native.is_file() and not dry_run:
+        return "missing-native"
+
+    out.parent.mkdir(parents=True, exist_ok=True)
+    if operation == "addition":
+        fmt = None if dry_run else ffprobe_format(native)
+        replay_addition(rec, native, out, events_dir, dry_run, fmt)
+    elif operation == "deletion":
+        replay_deletion(rec, native, out, dry_run)
+    elif operation == "modification":
+        replay_modification(rec, native, out, dry_run)
+    else:
+        return f"unknown-operation:{operation}"
+    return "ok"
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Rebuild anchor audio from manifest")
+    parser.add_argument("--manifest", default="metadata/media/anchor/anchor_manifest.jsonl")
+    parser.add_argument("--root", default=".", help="release root (contains audio/ + prepare/)")
+    parser.add_argument("--only", choices=["addition", "deletion", "modification"],
+                        help="process only this operation")
+    parser.add_argument("--overwrite", action="store_true")
+    parser.add_argument("--dry-run", action="store_true")
+    parser.add_argument("--limit", type=int, default=0, help="process at most N records (debug)")
+    args = parser.parse_args()
+
+    root = Path(args.root).resolve()
+    manifest_path = root / args.manifest
+    if not manifest_path.is_file():
+        print(f"ERROR: manifest not found: {manifest_path}", file=sys.stderr)
+        sys.exit(1)
+
+    records = read_jsonl(manifest_path)
+    if args.only:
+        records = [r for r in records if r["operation"] == args.only]
+    if args.limit:
+        records = records[:args.limit]
+
+    print(f"Processing {len(records)} anchor records (root={root})")
+    counts = {}
+    for rec in records:
+        status = process_record(rec, root, args.overwrite, args.dry_run)
+        counts[status] = counts.get(status, 0) + 1
+        if status not in ("ok", "skip"):
+            print(f"  [{status}] {rec['media_id']} ({rec['operation']})")
+
+    print("Summary:", counts)
+
+
+if __name__ == "__main__":
+    main()

prepare/unpack_audio.py

@@ -0,0 +1,144 @@
+#!/usr/bin/env python3
+"""Extract the release audio archives.
+
+For each bucket (native, anchor, events):
+  1. verify archive checksums against audio/CHECKSUMS.sha256 (when present)
+  2. if split, concatenate audio/audio_<bucket>.partNN.tar into
+     audio/audio_<bucket>.tar
+  3. extract the tar into audio/<bucket>/
+
+Self-contained: paths resolve relative to the release root (parent of
+prepare/).
+
+Usage:
+    python prepare/unpack_audio.py [--root ..] [--buckets native,anchor,events]
+                                   [--keep-tar] [--dry-run]
+"""
+
+import argparse
+import hashlib
+import re
+import sys
+import tarfile
+from pathlib import Path
+
+BUCKETS = ("native", "anchor", "events")
+
+
+def sha256_of(path: Path) -> str:
+    h = hashlib.sha256()
+    with open(path, "rb") as fh:
+        for chunk in iter(lambda: fh.read(8 * 1024 * 1024), b""):
+            h.update(chunk)
+    return h.hexdigest()
+
+
+def load_checksums(root: Path) -> dict[str, str]:
+    path = root / "audio" / "CHECKSUMS.sha256"
+    if not path.is_file():
+        return {}
+    out = {}
+    for line in path.read_text(encoding="utf-8").splitlines():
+        parts = line.split(None, 1)
+        if len(parts) == 2:
+            out[parts[1].strip()] = parts[0]
+    return out
+
+
+def find_parts(root: Path, bucket: str) -> list[Path]:
+    pattern = re.compile(rf"^audio_{bucket}\.part(\d+)\.tar$")
+    parts = []
+    for p in (root / "audio").iterdir():
+        m = pattern.match(p.name)
+        if m:
+            parts.append((int(m.group(1)), p))
+    return [p for _, p in sorted(parts)]
+
+
+def unpack_bucket(root: Path, bucket: str, checksums: dict, keep_tar: bool,
+                  dry_run: bool) -> bool:
+    parts = find_parts(root, bucket)
+    tar_path = root / "audio" / f"audio_{bucket}.tar"
+    if not parts:
+        if not tar_path.is_file():
+            print(f"audio_{bucket}: no parts found, skipping")
+            return False
+        print(f"audio_{bucket}: single tar")
+    else:
+        print(f"audio_{bucket}: {len(parts)} part(s)")
+
+    for part in parts:
+        expected = checksums.get(part.name)
+        if expected is None:
+            print(f"  WARN: no checksum for {part.name}")
+            continue
+        if dry_run:
+            continue
+        if sha256_of(part) != expected:
+            sys.exit(f"ERROR: checksum mismatch for {part.name}")
+    if not dry_run and checksums:
+        print("  checksums ok")
+
+    if parts:
+        if dry_run:
+            print(f"  [dry-run] reassemble -> {tar_path.name}, extract audio/{bucket}/")
+            return True
+        with open(tar_path, "wb") as out:
+            for part in parts:
+                with open(part, "rb") as fh:
+                    while True:
+                        data = fh.read(8 * 1024 * 1024)
+                        if not data:
+                            break
+                        out.write(data)
+        expected_tar = checksums.get(tar_path.name)
+        if expected_tar and sha256_of(tar_path) != expected_tar:
+            sys.exit(f"ERROR: checksum mismatch for reassembled {tar_path.name}")
+    else:
+        expected_tar = checksums.get(tar_path.name)
+        if not dry_run and expected_tar and sha256_of(tar_path) != expected_tar:
+            sys.exit(f"ERROR: checksum mismatch for {tar_path.name}")
+        if dry_run:
+            print(f"  [dry-run] extract audio/{bucket}/")
+            return True
+
+    with tarfile.open(tar_path, "r:") as tf:
+        members = tf.getnames()
+        if sys.version_info >= (3, 12):
+            tf.extractall(root, filter="data")
+        else:
+            tf.extractall(root)
+    print(f"  extracted {len(members)} files -> audio/{bucket}/")
+
+    if parts and not keep_tar:
+        tar_path.unlink()
+    return True
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Reassemble and extract release audio archives")
+    parser.add_argument("--root", type=Path, default=Path(__file__).resolve().parent.parent,
+                        help="release root (default: parent of prepare/)")
+    parser.add_argument("--buckets", default=",".join(BUCKETS),
+                        help="comma-separated subset of native,anchor,events")
+    parser.add_argument("--keep-tar", action="store_true",
+                        help="keep reassembled tar files after extraction")
+    parser.add_argument("--dry-run", action="store_true")
+    args = parser.parse_args()
+
+    root = args.root.resolve()
+    buckets = [b.strip() for b in args.buckets.split(",") if b.strip()]
+    for b in buckets:
+        if b not in BUCKETS:
+            sys.exit(f"ERROR: unknown bucket '{b}' (choose from {BUCKETS})")
+
+    checksums = load_checksums(root)
+    done = 0
+    for bucket in buckets:
+        if unpack_bucket(root, bucket, checksums, args.keep_tar, args.dry_run):
+            done += 1
+    print(f"Done. {done} bucket(s) unpacked.")
+
+
+if __name__ == "__main__":
+    main()