Identity
- Type
- startup
- Country label
- France
- HQ country
- France
- Founding country
- not in the notes
- Parent
- not in the notes
- Parent country
- not in the notes
- Country basis
- the research notes
Where this comes from
Convention D1: a dual label, HQ first, when the HQ, founding or parent country differ.
Models by Class
Models
Links
Organisation
pyannoteAIstartup, France
pyannoteAIstartup, FranceModelspyannote speaker-diarization-3.1pyannoteAI, speakerpyannote segmentation-3.0pyannoteAI, speakerpyannote Community-1pyannoteAI, speakerpyannote Precision-2pyannoteAI, speaker
pyannote speaker-diarization-3.1pyannoteAI, speakerpyannote segmentation-3.0pyannoteAI, speakerpyannote Community-1pyannoteAI, speakerpyannote Precision-2pyannoteAI, speakerUse Casesnone recorded
Who Runs Itnone recorded
Scores
| Benchmark | Model | Score | Who ran it | Setting |
|---|---|---|---|---|
| AMI (IHM, SDM) | pyannote Community-1 | 17 DER % | vendor-reported | AMI IHM, no collar, overlap scored |
| AMI (IHM, SDM) | pyannote Community-1 | 19.9 DER % | vendor-reported | AMI SDM, no collar, overlap scored |
| DIHARD 3 | pyannote Community-1 | 20.2 DER % | vendor-reported | full, no collar, overlap scored |
Where this comes from
Every recorded score of this organisation's models, with who ran it. Scores from different settings are not directly comparable.
Sources
- Top 7 Speaker Diarization APIs and Models in 2026 - pyannoteAI Speaker Intelligence and Diarization pyannote.ai https://www.pyannote.ai/blog/top-7-speaker-diarization-apis-and-models-in-2026
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "pyannoteAI", https://aurion.semai.id/organisations/pyannoteai/, records of October 2026.