metadata
title: README
emoji: 🚀
colorFrom: yellow
colorTo: green
sdk: static
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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.
Using it in production?
Consider switching to pyannoteAI for better and faster options.
| 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