| --- |
| license: cc-by-4.0 |
| task_categories: |
| - automatic-speech-recognition |
| - voice-activity-detection |
| tags: |
| - diarization |
| - speaker-diarization |
| - multi-speaker |
| - synthetic |
| - lhotse |
| - fastmss |
| pretty_name: FastMSS synthetic multi-speaker meetings |
| --- |
| |
| # FastMSS synthetic multi-speaker meetings |
|
|
| Synthetic multi-speaker conversational audio generated with [FastMSS](https://github.com/argmaxinc/FastMSS-internal). Each split contains mixture WAVs (16 kHz, mono), Lhotse manifests (recordings / supervisions / cuts), and per-mixture RTTM files with word-level speaker labels. |
|
|
| ## Splits / subfolders |
|
|
| - **`debug/`** — 1 mixtures, 1.6 min total, 6 unique speakers |
| - **`v0.1/`** — 1000 mixtures, 1546.0 min total, 40 unique speakers |
|
|
| ## Per-split layout |
|
|
| ``` |
| <split>/ |
| audio/<recording_id>.wav # 16 kHz mono mixture |
| manifests/ |
| synth-*-train-recordings.jsonl.gz |
| synth-*-train-supervisions.jsonl.gz |
| synth-*-train-cuts.jsonl.gz # the file you want for training |
| all_cuts.jsonl.gz # source utterances used by the sim |
| all_rooms.json # RIR room metadata |
| noise_files.txt # noise files used |
| rttm_word/<recording_id>.rttm # word-level SPEAKER lines |
| sim.log # generator log |
| ``` |
|
|
| ## Loading |
|
|
| ```python |
| from huggingface_hub import snapshot_download |
| from lhotse import CutSet |
| import os |
| |
| local = snapshot_download("<user-or-org>/<repo-name>", repo_type="dataset") |
| os.chdir(os.path.join(local, 'v0.1')) # or 'debug' |
| cuts = CutSet.from_file('manifests/synth-librispeech-train-cuts.jsonl.gz') |
| for cut in cuts: |
| audio = cut.load_audio() # path is resolved relative to cwd |
| ... |
| ``` |
|
|
| ## Generation |
|
|
| See the [FastMSS repo](https://github.com/argmaxinc/FastMSS-internal) for the exact simulator config. Each split contains its own `sim.log` for the full generator output. |
|
|
