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README.md

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+---
+language:
+- en
+task_categories:
+- automatic-speech-recognition
+- text-generation
+- audio-classification
+tags:
+- spoken-dialogue
+- full-duplex
+- turn-taking
+- interruption
+- backchannel
+pretty_name: InteractSpeech English Text and Timeline
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/*.parquet
+---
+
+# InteractSpeech: English Text-and-Timeline Release
+
+This is the English text-and-timeline release associated with **InteractSpeech: A Speech Dialogue Interaction Corpus for Spoken Dialogue Model** (Findings of EMNLP 2025).
+
+InteractSpeech is designed for real-time spoken-dialogue interaction, including interruptions, backchannels, pauses, gaps, overlaps, and turn transitions. The paper describes an approximately 150-hour English corpus containing 90,000 text utterances.
+
+## Release contents
+
+| Item | Value |
+| --- | ---: |
+| Training records | 59,020 |
+| Parquet shards | 3 |
+| Audio waveforms | Not included |
+| Video assets | Not included |
+
+The release preserves dialogue text, speaker timing, interaction events, overlap regions, complete interrupted utterances, quality metadata, and per-utterance TTS reconstruction specifications. Audio can be regenerated with any TTS system while preserving each published segment duration and the global dialogue timeline.
+
+## Data format
+
+Each Parquet row contains:
+
+| Column | Description |
+| --- | --- |
+| `id` | Public record identifier |
+| `view` | Dataset view |
+| `category` | Dataset category |
+| `record_json` | Complete record serialized as JSON |
+
+```python
+import json
+import pyarrow.parquet as pq
+
+table = pq.read_table("data/train-00000.parquet", columns=["record_json"])
+sample = json.loads(table["record_json"][0].as_py())
+```
+
+The decoded record contains:
+
+- `turns`: the training dialogue with timestamps and input-speech reconstruction recipes;
+- `meta`: dialogue-level language, topic, event counts, and truncation information;
+- `source_record`: the preserved InteractionSpeech dialogue, event annotations, full utterances, overlap regions, and source-to-training turn mapping.
+
+For each input-speech segment, synthesize the text in `audio_in.source.transcript` using a consistent voice for the same `voice_key`, then fit it to `reference_duration_ms`. Do not alter the published global `start_ms` and `end_ms` values.
+
+## Citation
+
+```bibtex
+@inproceedings{chen-etal-2025-interactspeech,
+    title = {{I}nteract{S}peech: A Speech Dialogue Interaction Corpus for Spoken Dialogue Model},
+    author = {Chen, Yifu and Ji, Shengpeng and Wang, Ziqing and Wang, Hanting and Zhao, Zhou},
+    booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2025},
+    month = nov,
+    year = {2025},
+    address = {Suzhou, China},
+    publisher = {Association for Computational Linguistics},
+    pages = {8024--8033},
+    doi = {10.18653/v1/2025.findings-emnlp.424},
+    url = {https://aclanthology.org/2025.findings-emnlp.424/}
+}
+```
+
+- Paper: https://aclanthology.org/2025.findings-emnlp.424/
+- Project page and audio examples: https://interactspeech.github.io/

data/train-00000.parquet

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+oid sha256:180cc47c2a1316d26e975a38b52d9f34c8943d2cc2d452303902d98ae0faaa91
+size 18454736

data/train-00001.parquet

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+oid sha256:d55d778da60ec868fce63395c625f1db8b8127eb3bb013330d01835c8ccdba3a
+size 76485365

data/train-00002.parquet

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+oid sha256:dabf93e21ac1cd6c87e35c6f0cece50f5a036353fac906e25f20e722508a1c11
+size 1611989

dataset_info.json

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+{
+  "dataset": "InteractSpeech",
+  "subset": "English text and timeline",
+  "schema": "interactspeech_text_timeline_v1",
+  "rows": 59020,
+  "parquet_shards": [
+    {
+      "path": "data/train-00000.parquet",
+      "rows": 9849,
+      "bytes": 18454736
+    },
+    {
+      "path": "data/train-00001.parquet",
+      "rows": 48144,
+      "bytes": 76485365
+    },
+    {
+      "path": "data/train-00002.parquet",
+      "rows": 1027,
+      "bytes": 1611989
+    }
+  ],
+  "audio_waveforms_included": false,
+  "tts_reconstructable": true
+}