Voice Activity Detection
pyannote.audio
pyannote
pyannote-audio-pipeline
audio
voice
speech
speaker
speaker-diarization
speaker-change-detection
overlapped-speech-detection
Instructions to use hbredin/api-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- pyannote.audio
How to use hbredin/api-test with pyannote.audio:
from pyannote.audio import Pipeline pipeline = Pipeline.from_pretrained("hbredin/api-test") # 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
File size: 917 Bytes
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tags:
- pyannote
- pyannote-audio
- pyannote-audio-pipeline
- audio
- voice
- speech
- speaker
- speaker-diarization
- speaker-change-detection
- voice-activity-detection
- overlapped-speech-detection
---
# `pyannoteAI` premium speaker diarization
*Warning:* this is a work in progress, though it should already be functional.
1. Create an API key on [`pyannoteAI` dashboard](https://dashboard.pyannote.ai).
2. Install `pyannote.audio` 4.x (yet to be released but `develop` branch should do).
3. Enjoy `pyannoteAI` premium speaker diarization pipeline by changing one single line of code!
```diff
from pyannote.audio import Pipeline
- pipeline = Pipeline.from_pretrained('pyannote/speaker-diarization-3.1', token="{huggingface-token}")
+ pipeline = Pipeline.from_pretrained('hbredin/api-test', token="{pyannoteAI-api-key}")
diarization = pipeline("/path/to/audio.wav")
```
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