DJRHails/pyannote-embedding-librispeech

Pre-computed speaker embeddings Pre-computed 512-dim L2-normalized speaker embeddings extracted with pyannote/embedding over LibriSpeech train.100 + train.360 (1172 speakers via openslr/librispeech_asr). One utterance per speaker, minimum 3 s duration. Contents librispeech.pyannote-embedding.npz — numpy .npz archive with: embeddings: (3507, 512) float32 speaker_ids: (3507,) string IDs from the source corpus metadata_json: per-speaker metadata (accent / age /… See the full description on the dataset page: https://huggingface.co/datasets/DJRHails/pyannote-embedding-librispeech.