Automatic Speech Recognition
pyannote.audio
pyannote
pyannote-audio-pipeline
audio
voice
speech
speaker
speaker-diarization
speaker-change-detection
voice-activity-detection
overlapped-speech-detection
Instructions to use beclab/speaker-diarization-community-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- pyannote.audio
How to use beclab/speaker-diarization-community-1 with pyannote.audio:
from pyannote.audio import Pipeline pipeline = Pipeline.from_pretrained("beclab/speaker-diarization-community-1") # inference on the whole file pipeline("file.wav") # inference on an excerpt from pyannote.core import Segment excerpt = Segment(start=2.0, end=5.0) from pyannote.audio import Audio waveform, sample_rate = Audio().crop("file.wav", excerpt) pipeline({"waveform": waveform, "sample_rate": sample_rate}) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e01252ffc8647a760bccc5645cc7b01a7163b349662138cf7eaf31186bd93fd
- Size of remote file:
- 26.6 MB
- SHA256:
- 6f10ff60898a1d185fa22e1d11e0bfa8a92efec811f11bca48cb8cafebefd929
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