metadata
tags:
- pyannote
- audio
- voice
- speech
- speaker
- speaker-diarization
- speaker-change-detection
- voice-activity-detection
- overlapped-speech-detection
datasets:
- ami
- dihard
- voxconverse
- voxceleb
license: mit
inference: false
pyannote.audio // speaker diarization
Relies on pyannote.audio 2.0 currently in development: see installation instructions.
from pyannote.audio import Pipeline
pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization")
output = pipeline("audio.wav")
for turn, _, speaker in output.itertracks(yield_label=True):
# speaker speaks between turn.start and turn.end
...
Benchmark
| Dataset | Diarization error rate |
|---|---|
AMI only_words evaluation set |
21.3% |
| DIHARD 3 evaluation set | 22.2% |
| VoxConverse 0.0.2 evaluation set | 13.0% |
Support
For commercial enquiries and scientific consulting, please contact me.
For technical questions and bug reports, please check pyannote.audio Github repository.
Citation
@inproceedings{Bredin2020,
Title = {{pyannote.audio: neural building blocks for speaker diarization}},
Author = {{Bredin}, Herv{\'e} and {Yin}, Ruiqing and {Coria}, Juan Manuel and {Gelly}, Gregory and {Korshunov}, Pavel and {Lavechin}, Marvin and {Fustes}, Diego and {Titeux}, Hadrien and {Bouaziz}, Wassim and {Gill}, Marie-Philippe},
Booktitle = {ICASSP 2020, IEEE International Conference on Acoustics, Speech, and Signal Processing},
Address = {Barcelona, Spain},
Month = {May},
Year = {2020},
}