pyannote.audio
PyTorch
TensorBoard
pyannote
pyannote-audio-model
audio
voice
speech
speaker
speaker-recognition
speaker-verification
speaker-identification
speaker-embedding
Instructions to use pyannote/embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- pyannote.audio
How to use pyannote/embedding with pyannote.audio:
from pyannote.audio import Model, Inference model = Model.from_pretrained("pyannote/embedding") 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
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The collected information will help acquire a better knowledge of pyannote.audio userbase and help its maintainers apply for grants to improve it further. If you are an academic researcher, please cite the relevant papers in your own publications using the model. If you work for a company, please consider contributing back to pyannote.audio development (e.g. through unrestricted gifts). We also provide scientific consulting services around speaker diarization and machine listening.
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