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 DroolingPanda/speaker-diarization-community-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- pyannote.audio
How to use DroolingPanda/speaker-diarization-community-1 with pyannote.audio:
from pyannote.audio import Pipeline pipeline = Pipeline.from_pretrained("DroolingPanda/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
Create README.md
Browse files- plda/README.md +3 -0
plda/README.md
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PLDA model trained by [BUT Speech@FIT](https://speech.fit.vut.cz/) group.
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Thanks to [Jiangyu Han](https://github.com/jyhan03) and [Petr Pálka](https://github.com/Selesnyan) for the integration of VBx in pyannote.audio.
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