| --- |
| license: cc-by-sa-4.0 |
| language: |
| - km |
| pretty_name: FastMSS Khmer Meeting Simulation |
| size_categories: |
| - 1K<n<10K |
| tags: |
| - speaker-diarization |
| - multi-speaker |
| - meeting-simulation |
| - fastmss |
| - khmer |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: metadata/train.jsonl |
| - split: dev |
| path: metadata/dev.jsonl |
| - split: test |
| path: metadata/test.jsonl |
| --- |
| |
| # FastMSS Khmer Meeting Simulation |
|
|
| This dataset contains **6,900 simulated Khmer multi-speaker meetings** |
| (**130.37 hours**) generated with |
| [FastMSS](https://github.com/popcornell/FastMSS) from the |
| [Digital-Divide-Data/khmer-speech-dataset](https://huggingface.co/datasets/Digital-Divide-Data/khmer-speech-dataset) |
| speech corpus. |
|
|
| The meetings are intended for **speaker diarization research**, especially for |
| experimenting with Khmer data when real multi-speaker meeting recordings are not |
| available. |
|
|
| > **Important:** these are synthetic, clean, read-speech meetings, not real |
| > conversational recordings. They contain only 20 source speakers and were |
| > generated without reverberation, background noise, or FIR filtering. Results |
| > on this dataset should not be treated as evidence of real-world performance. |
|
|
| ## At a glance |
|
|
| | Item | Value | |
| |---|---| |
| | Language | Khmer (`km`) | |
| | Meetings | 6,900 | |
| | Audio | 130.37 hours | |
| | Speakers | 20 | |
| | Speakers per meeting | 2, 3, or 4 | |
| | Topics | 69 | |
| | Sample rate | 16 kHz | |
| | Channels | Mono | |
| | Audio format | WAV, 16-bit PCM | |
| | Annotation | RTTM + JSONL metadata | |
| | Per-speaker stems | Not included | |
|
|
| ## Source data and generation |
|
|
| The source speech is the **Cultural Khmer ASR Dataset**: |
|
|
| - Dataset: <https://huggingface.co/datasets/Digital-Divide-Data/khmer-speech-dataset> |
| - License: **CC BY-SA 4.0** |
|
|
| Meetings were generated with **FastMSS**: |
|
|
| - Code: <https://github.com/popcornell/FastMSS> |
| - Recipe: `FastMSS/recipes/khmer.yaml` |
| - Source manifests: one Lhotse manifest per topic, then combined for simulation |
|
|
| The simulation used these settings: |
|
|
| - 100 meetings per topic, 69 topics |
| - 2–4 speakers per meeting, at most 4 concurrent speakers |
| - 60 s target duration; actual meetings are 60–318 s because turn-taking extends the target |
| - 16 kHz mono output |
| - `reverberate: false` |
| - `add_noise: false` |
| - `use_fir: false` |
| - `save_rttm: true` |
| - Flat turn-taking priors, with interruptions and backchannels producing overlap |
|
|
| RTTMs were generated from the simulation's aligned speech segments. Same-speaker |
| segments separated by **0.2 s or less** were merged. This is why the number of |
| RTTM segments differs from the number of utterance-level manifest segments. |
|
|
| See [`ATTRIBUTION.md`](ATTRIBUTION.md) for source and tool attribution. |
|
|
| ## Splits |
|
|
| The split is a **designated-speaker holdout**: |
|
|
| - Train: 6,207 meetings / 117.18 h / 16 speakers |
| - Dev: 611 meetings / 11.50 h / 17 speakers |
| - Test: 82 meetings / 1.70 h / 16 speakers |
|
|
| No designated dev or test speaker appears in a training meeting. However, the |
| underlying speech cuts are reused across topics and splits: |
|
|
| - 451 source cuts overlap train and dev |
| - 39 source cuts overlap train and test |
|
|
| This is not a fully source-cut-disjoint split. Keep that in mind when interpreting |
| very high scores. |
|
|
| | Split | Meetings | Hours | Speakers in meetings | Source cuts | Manifest segments | RTTM segments | 2-spk | 3-spk | 4-spk | |
| |---|---:|---:|---:|---:|---:|---:|---:|---:|---:| |
| | train | 6,207 | 117.176 | 16 | 49,542 | 58,556 | 50,972 | 2,105 | 2,149 | 1,953 | |
| | dev | 611 | 11.497 | 17 | 5,511 | 6,053 | 5,318 | 127 | 228 | 256 | |
| | test | 82 | 1.699 | 16 | 604 | 715 | 604 | 17 | 34 | 31 | |
| | **total** | **6,900** | **130.373** | **20** | **55,151** | **65,324** | **56,894** | **2,249** | **2,411** | **2,240** | |
|
|
| Overlap statistics are provided in `metadata/stats.json`: |
|
|
| - `overlap_ratio` = overlap seconds / union of speech seconds |
| - `overlap_fraction` = overlap seconds / meeting duration |
|
|
| Dataset-wide mean `overlap_ratio` is **0.2023** (p95 **0.4038**); mean |
| `overlap_fraction` is **0.1955** (p95 **0.3919**). |
|
|
| ## Files |
|
|
| ```text |
| audio/ |
| <meeting_id>.wav |
| rttm/ |
| train/<meeting_id>.rttm |
| dev/<meeting_id>.rttm |
| test/<meeting_id>.rttm |
| metadata/ |
| train.jsonl |
| dev.jsonl |
| test.jsonl |
| stats.json |
| split.json |
| source_validation.json |
| ``` |
|
|
| Every WAV is a mono 16 kHz meeting mixture. Every RTTM uses the standard |
| `SPEAKER` format with speaker labels such as `f-adt1-0001` and `m-adt2-0002`. |
|
|
| ## Metadata schema |
|
|
| Each JSONL line describes one meeting: |
|
|
| ```json |
| { |
| "meeting_id": "00150280-3181-4e63-b7e1-6aae3e7ffe45", |
| "split": "train", |
| "audio": "audio/00150280-3181-4e63-b7e1-6aae3e7ffe45.wav", |
| "rttm": "rttm/train/00150280-3181-4e63-b7e1-6aae3e7ffe45.rttm", |
| "duration": 60.0, |
| "sampling_rate": 16000, |
| "channels": 1, |
| "topic": "wildlife-condition-in-cambodia", |
| "num_speakers": 3, |
| "speakers": ["f-adt2-0002", "m-adt1-0004", "m-adt2-0002"], |
| "num_segments": 9, |
| "num_rttm_segments": 8, |
| "speech_seconds": 58.0, |
| "overlap_seconds": 5.0, |
| "overlap_ratio": 0.086, |
| "overlap_fraction": 0.083, |
| "segments": [ |
| { |
| "start": 0.9115, |
| "end": 7.9415, |
| "speaker": "m-adt2-0002", |
| "text": "...", |
| "transition_type": "FIRST", |
| "source_cut_id": "train-...", |
| "speech_level_db": -22.97 |
| } |
| ] |
| } |
| ``` |
|
|
| `segments` are **utterance-level** supervisions from the FastMSS manifest and |
| include the Khmer transcript and source-cut metadata. The RTTM is the diarization |
| reference and may merge adjacent same-speaker segments. Use the RTTM for |
| diarization scoring; use `segments` when you need transcripts or source-cut |
| provenance. |
|
|
| ## Loading |
|
|
| The JSONL stores paths relative to the dataset root. Download a snapshot and |
| resolve them locally: |
|
|
| ```python |
| import json |
| from pathlib import Path |
| |
| from huggingface_hub import snapshot_download |
| |
| root = Path( |
| snapshot_download( |
| "Panhapich/fastmss_meeting_simulation", |
| repo_type="dataset", |
| ) |
| ) |
| |
| records = [ |
| json.loads(line) |
| for line in (root / "metadata" / "train.jsonl").open(encoding="utf-8") |
| ] |
| meeting = records[0] |
| wav_path = root / meeting["audio"] |
| rttm_path = root / meeting["rttm"] |
| ``` |
|
|
| With `datasets`, you can load the metadata directly: |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset( |
| "Panhapich/fastmss_meeting_simulation", |
| data_files={ |
| "train": "metadata/train.jsonl", |
| "dev": "metadata/dev.jsonl", |
| "test": "metadata/test.jsonl", |
| }, |
| ) |
| ``` |
|
|
| The `audio` and `rttm` columns remain relative paths; prefix them with the local |
| dataset root before opening the files. |
|
|
| ## Intended use and limitations |
|
|
| Suitable for: |
|
|
| - Khmer speaker diarization experiments |
| - Pipeline and scoring smoke tests |
| - Comparing diarization systems under controlled overlap |
| - Studying the effect of simulated conversational data |
|
|
| Not suitable for: |
|
|
| - Claims about real Khmer meeting performance |
| - Commercial deployment without a separate license review |
| - Speaker extraction or separation benchmarks requiring per-speaker references |
| - Evaluating robustness to noise, reverberation, far-field microphones, or |
| spontaneous conversational speech |
|
|
| Main limitations: |
|
|
| - Only 20 source speakers |
| - Clean, close-talk, read speech |
| - No noise, reverberation, or FIR filtering |
| - Source cuts overlap across splits |
| - No per-speaker stems |
| - Synthetic turn-taking may not match real meeting dynamics |
|
|
| ## License and attribution |
|
|
| The dataset is released under **CC BY-SA 4.0**, following the source corpus |
| license. See [`LICENSE`](LICENSE) and [`ATTRIBUTION.md`](ATTRIBUTION.md). |
|
|
| If you use this dataset, please also cite FastMSS: |
|
|
| ```bibtex |
| @unpublished{polok2026mindthegap, |
| author = {Polok, Alexander and Medennikov, Ivan and Watanabe, Shinji and |
| {\v{C}}ernock{\'y}, Jan and Burget, Luk{\'a}{\v{s}} and |
| Cornell, Samuele}, |
| title = {Mind the Gap: Impact of Synthetic Conversational Data on |
| Multi-Talker {ASR} and Speaker Diarization}, |
| note = {Submitted to INTERSPEECH}, |
| year = {2026} |
| } |
| ``` |
|
|
