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pyannote.audio

non-profit
https://github.com/pyannote/pyannote-audio
pyannote
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AI & ML interests

speaker diarization // speaker recognition // speaker segmentation // voice activity detection // overlapped speech detection // speaker change detection

Recent Activity

hbredin  updated a Space about 12 hours ago
pyannote/README
hbredin  updated a Space about 12 hours ago
pyannote/README
hbredin  updated a model 3 months ago
pyannote/speech-separation-ami-1.0
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pyannote.audio is an open-source toolkit for speaker diarization.

Pretrained pipelines reach state-of-the-art performance on most academic benchmarks.
Training is made possible thanks to Jean Zay supercomputer.

pyannoteAI provides even better and faster enterprise options, which can be tried for free on our playground.

Benchmark v2.1 v3.1 pyannoteAI
AISHELL-4 14.1 12.2 11.2
AliMeeting (channel 1) 27.4 24.4 19.3
AMI (IHM) 18.9 18.8 15.8
AMI (SDM) 27.1 22.4 19.3
AVA-AVD 66.3 50.0 44.8
CALLHOME (part 2) 31.6 28.4 19.8
DIHARD 3 (full) 26.9 21.7 16.8
Earnings21 17.0 9.4 9.1
Ego4D (dev.) 61.5 51.2 44.0
MSDWild 32.8 25.3 19.8
RAMC 22.5 22.2 11.1
REPERE (phase2) 8.2 7.8 7.6
VoxConverse (v0.3) 11.2 11.3 9.8
Diarization error rate (in %)

Using high-end NVIDIA hardware,

  • v2.1 takes around 1m30s to process 1h of audio
  • v3.1 takes around 1m20s to process 1h of audio
  • On-premise pyannoteAI takes less than 30s to process 1h of audio

datasets

None public yet