Speaker Diarization On Etape
Métriques
DER(%)
FA
Miss
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | DER(%) | FA | Miss | Paper Title | Repository |
|---|---|---|---|---|---|
| Baseline | 7.7 | 7.5 | 0.2 | pyannote.audio: neural building blocks for speaker diarization | |
| pyannote (MFCC) | 5.6 | 5.2 | 0.4 | pyannote.audio: neural building blocks for speaker diarization | |
| pyannote (waveform) | 4.9 | 4.2 | 0.7 | pyannote.audio: neural building blocks for speaker diarization |
0 of 3 row(s) selected.