22 releases
| 0.3.0 | Dec 13, 2024 |
|---|---|
| 0.3.0-beta.0 | Nov 30, 2024 |
| 0.2.9 | Nov 29, 2024 |
| 0.2.7 | Aug 18, 2024 |
| 0.1.9 | Aug 7, 2024 |
#206 in Machine learning
174 downloads per month
16KB
232 lines
pyannote-rs
Pyannote audio diarization in Rust
Features
- Compute 1 hour of audio in less than a minute on CPU.
- Faster performance with DirectML on Windows and CoreML on macOS.
- Accurate timestamps with Pyannote segmentation.
- Identify speakers with wespeaker embeddings.
Install
cargo add pyannote-rs
Usage
See Building
Examples
See examples
How it works
pyannote-rs uses 2 models for speaker diarization:
- Segmentation: segmentation-3.0 identifies when speech occurs.
- Speaker Identification: wespeaker-voxceleb-resnet34-LM identifies who is speaking.
Inference is powered by onnxruntime.
- The segmentation model processes up to 10s of audio, using a sliding window approach (iterating in chunks).
- The embedding model processes filter banks (audio features) extracted with knf-rs.
Speaker comparison (e.g., determining if Alice spoke again) is done using cosine similarity.
Credits
Big thanks to pyannote-onnx and kaldi-native-fbank
Dependencies
~3–10MB
~108K SLoC