Voice Activity Detection
pyannote.audio
PyTorch
pyannote
pyannote-audio-model
audio
voice
speech
speaker
speaker-diarization
speaker-change-detection
speaker-segmentation
overlapped-speech-detection
resegmentation
Instructions to use objects76/speaker-diarization-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- pyannote.audio
How to use objects76/speaker-diarization-v1 with pyannote.audio:
from pyannote.audio import Model, Inference model = Model.from_pretrained("objects76/speaker-diarization-v1") inference = Inference(model) # inference on the whole file inference("file.wav") # inference on an excerpt from pyannote.core import Segment excerpt = Segment(start=2.0, end=5.0) inference.crop("file.wav", excerpt) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a8c3c55316c69d94c01139413d14aaaa3d6a743d9a741cf06d81c9f1ac629fca
- Size of remote file:
- 5.91 MB
- SHA256:
- 400772bf399e3a9e60443ebd9bb939518c2cf4d1e79dc4b48b41cbea4c719f22
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