| |
| """Writes a mock scoring trace for the trace dashboard (static/trace.html) and its schema (docs/trace-schema.ts). |
| |
| Usage: python scripts/mock_trace.py # -> static/assets/trace-mock.json |
| python scripts/mock_trace.py --out other.json |
| |
| Not a hand-written JSON: the real Scorer scores synthetic posteriors and energy, so every field is what the pipeline |
| produces. The recording is a learner saying وين سيدك؟ سيدي قعد في بيته (a bank sentence with several accepted |
| readings: سيدي / جدّي, بيت / بيت with the diphthong), with what the dashboard should show planted in it: |
| - ع of قعد said as a glottal stop (ء): flagged, with a severity-3 tip, and raised by a teacher's calibration floor |
| - a spike of h in a near-silent frame two frames after the short a of سيدك, inside the a's window and the k's |
| (the window runs from the end of the sound before to the start of the one after) |
| - k at the end of سيدك weak, as the native TTS voice's is too: the native baseline raises it |
| """ |
| from __future__ import annotations |
|
|
| import argparse |
| import json |
| import sys |
| from pathlib import Path |
|
|
| import numpy as np |
|
|
| sys.path.insert(0, str(Path(__file__).resolve().parent.parent)) |
|
|
| from app.phrases import PHRASES |
| from app.scorer import Reference, Scorer, Vocab |
|
|
| SYMS = ["<pad>", "w", "eː", "n", "s", "iː", "d", "a", "k", "i", "ʔ", "ʕ", "f", "b", "t", "o", "dʒ", "j", "q", "g", |
| "h", "χ", "e", "u", "tʃ", "r", "l", "m", "ħ"] |
| VOCAB = {s: i for i, s in enumerate(SYMS)} |
| PHRASE = next(p for p in PHRASES if p["he"].startswith("איפה סבא שלך")) |
|
|
| |
| GAP, PAUSE = ("-", 0.95, 2, 0.15), ("-", 0.97, 6, 0.03) |
| SAID = [ |
| ("-", 0.97, 4, 0.02), |
| ("w", 0.85, 2, 0.55), GAP, ("eː", 0.9, 4, 1.0), GAP, ("n", 0.8, 2, 0.5), PAUSE, |
| ("s", 0.9, 3, 0.45), GAP, ("iː", 0.88, 4, 0.95), GAP, ("d", 0.8, 2, 0.5), GAP, |
| ("a", 0.45, 1, 0.85), ("-", 0.9, 1, 0.2), ("h", 0.96, 1, 0.04), ("-", 0.9, 1, 0.1), |
| ("k", 0.3, 2, 0.4), ("-", 0.8, 1, 0.1), PAUSE, |
| ("s", 0.9, 3, 0.45), GAP, ("iː", 0.9, 4, 0.95), GAP, ("d", 0.85, 2, 0.5), GAP, ("i", 0.8, 2, 0.8), PAUSE, |
| ("ʔ", 0.82, 2, 0.4), GAP, ("a", 0.85, 2, 0.9), GAP, ("ʔ", 0.8, 2, 0.35), GAP, |
| ("a", 0.85, 2, 0.9), GAP, ("d", 0.85, 2, 0.5), PAUSE, |
| ("f", 0.85, 3, 0.35), GAP, ("i", 0.85, 2, 0.8), PAUSE, |
| ("b", 0.85, 2, 0.5), GAP, ("eː", 0.9, 4, 1.0), GAP, ("t", 0.85, 2, 0.45), GAP, ("o", 0.85, 3, 0.85), |
| ("-", 0.97, 4, 0.02), |
| ] |
|
|
|
|
| def emissions() -> tuple[np.ndarray, np.ndarray]: |
| rows, energy = [], [] |
| for sym, p, frames, e in SAID: |
| for _ in range(frames): |
| r = np.full(len(SYMS), (1 - p) / (len(SYMS) - 1)) |
| r[VOCAB["<pad>" if sym == "-" else sym]] = p |
| rows.append(r) |
| energy.append(e) |
| return np.log(np.array(rows)), np.array(energy) |
|
|
|
|
| def main() -> int: |
| ap = argparse.ArgumentParser(description=__doc__.splitlines()[0]) |
| ap.add_argument("--out", type=Path, default=Path(__file__).resolve().parent.parent / "static/assets/trace-mock.json") |
| args = ap.parse_args() |
|
|
| logp, energy = emissions() |
| scorer = Scorer(lambda wav: logp, Vocab(VOCAB)) |
| scorer.set_calibrations([{"expected": "ʕ", "heard": "ʔ", "floor": 45, "scope": "global"}]) |
| |
| toks = scorer._variants(PHRASE)[0][3] |
| ref = Reference([(t.word, t.sound) for t in toks], |
| [55.0 if (t.word, t.sound) == (1, "K") else 100.0 for t in toks]) |
| result = scorer.score_logp(logp, PHRASE, [ref], diagnostics=True, duration_s=len(logp) * 0.02, energy=energy) |
| result["phrase"] = {"he": PHRASE["he"], "ar": PHRASE["variants"][0][0]} |
| args.out.write_text(json.dumps(result, ensure_ascii=False, indent=1), encoding="utf-8") |
| print(f"{args.out}: score {result['score']}, {len(result['trace']['tokens'])} sounds, " |
| f"{len(result['trace']['variants'])} candidate readings, {result['trace']['frames']['count']} frames") |
| return 0 |
|
|
|
|
| if __name__ == "__main__": |
| sys.exit(main()) |
|
|
