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 paris-iea/speaker-diarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- pyannote.audio
How to use paris-iea/speaker-diarization with pyannote.audio:
from pyannote.audio import Pipeline pipeline = Pipeline.from_pretrained("paris-iea/speaker-diarization") # 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
Download technical_report_2.1.pdf from paris-iea/speaker-diarization: direct link, hf CLI and curl.
- Browser
- Download file 372 kB
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https://huggingface.co/paris-iea/speaker-diarization/resolve/main/technical_report_2.1.pdf
- Command line
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hf download hf://paris-iea/speaker-diarization/technical_report_2.1.pdf
-
curl -L -o technical_report_2.1.pdf https://huggingface.co/paris-iea/speaker-diarization/resolve/main/technical_report_2.1.pdf
372 kB