StillScript mirror of pyannote/speaker-diarization-community-1
This repository is an unmodified redistribution of
pyannote/speaker-diarization-community-1,
re-hosted so that StillScript Confidential Transcripts
can fetch it without each end user having to individually accept the upstream
repository's gating conditions.
License, Attribution, and Citation Information
- Title:
speaker-diarization-community-1 - Author: Hervé Bredin and the pyannoteAI / pyannote.audio team
- Source: https://huggingface.co/pyannote/speaker-diarization-community-1
- License: Creative Commons Attribution 4.0 International (CC-BY-4.0)
CC-BY-4.0 permits redistribution provided attribution is given and changes are indicated.
Changes made
None to the model itself. The pipeline weights, the config.yaml, and the
component sub-models (segmentation/, embedding/, plda/) are byte-for-byte
identical to the upstream repository. The only differences are:
- this README (replacing the upstream model card), and
- the removal of the upstream
diarization.gifillustration and.gitattributes, neither of which is used at inference time.
No retraining, fine-tuning, quantisation, or conversion of any kind was performed.
Verifying that for yourself
Every shipped file's SHA-256, as redistributed here:
| File | SHA-256 |
|---|---|
config.yaml | 5ce2bfa9a938dc132cec1172592d65173cbb8f444ea1e4133f10f9391de155be |
segmentation/pytorch_model.bin | 7ad24338d844fb95985486eb1a464e32d229f6d7a03c9abe60f978bacf3f816e |
embedding/pytorch_model.bin | 6f10ff60898a1d185fa22e1d11e0bfa8a92efec811f11bca48cb8cafebefd929 |
plda/plda.npz | 9b77bcd840692710dd3496f62ecfeed8d8e5f002fd991b785079b244eab7d255 |
plda/xvec_transform.npz | 325f1ce8e48f7e55e9c8aa47e05d2766b7c48c4b25b8de8dd751e7a4cc5fbe8f |
StillScript pins these same hashes and verifies them after download.
Citations
The original authors ask that the following be cited. Reproduced verbatim from the upstream model card.
- Speaker segmentation model
@inproceedings{Plaquet23,
author={Alexis Plaquet and Hervé Bredin},
title={{Powerset multi-class cross entropy loss for neural speaker diarization}},
year=2023,
booktitle={Proc. INTERSPEECH 2023},
}
pyannote.audiotoolkit
@inproceedings{Bredin23,
author={Hervé Bredin},
title={{pyannote.audio 2.1 speaker diarization pipeline: principle, benchmark, and recipe}},
year=2023,
booktitle={Proc. INTERSPEECH 2023},
}
Please prefer the upstream repository if you are not using StillScript — it is the canonical source, and using it directly supports the pyannote project.
Mirrored by Acutus Consulting for StillScript Confidential Transcripts. Modelling credit: the pyannote.audio / pyannoteAI team.