Voice Activity Detection
pyannote.audio
pyannote
pyannote-audio-pipeline
audio
voice
speech
speaker
speaker-diarization
speaker-change-detection
overlapped-speech-detection
Instructions to use pyannote/speaker-diarization-precision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- pyannote.audio
How to use pyannote/speaker-diarization-precision with pyannote.audio:
from pyannote.audio import Pipeline pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization-precision") # 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
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Download README.md from pyannote/speaker-diarization-precision: direct link, hf CLI and curl.
- Browser
- Download file 1.41 kB
-
https://huggingface.co/pyannote/speaker-diarization-precision/resolve/main/README.md
- Command line
-
hf download hf://pyannote/speaker-diarization-precision/README.md
-
curl -L -o README.md https://huggingface.co/pyannote/speaker-diarization-precision/resolve/main/README.md
1.41 kB
metadata
tags:
- pyannote
- pyannote-audio
- pyannote-audio-pipeline
- audio
- voice
- speech
- speaker
- speaker-diarization
- speaker-change-detection
- voice-activity-detection
- overlapped-speech-detection
Precision speaker diarization
This pipeline runs Precision speaker diarization on pyannoteAI cloud.
Read the announcement blog post.
This pipeline is a stripped down version of pyannoteAI SDK that provides much more features:
- speaker diarization optimized for speech-to-text
- speaker voiceprinting and identification
- confidence scores
- and more...
A self-hosted version of Precision is also available for enterprise customers.
Setup
pip install pyannote.audio- Create an API key on
pyannoteAIdashboard (free credits included)
Usage
# initialize speaker diarization pipeline
from pyannote.audio import Pipeline
pipeline = Pipeline.from_pretrained(
'pyannote/speaker-diarization-precision',
token="{pyannoteAI-api-key}")
# run speaker diarization on pyannoteAI cloud
output = pipeline("/path/to/audio.wav")
# enjoy state-of-the-art speaker diarization
for turn, speaker in output.speaker_diarization:
print(f"start={turn.start:.1f}s stop={turn.end:.1f}s speaker_{speaker}")