Detail aplikovaného výsledku

DiariZen

HAN, J.; PÁLKA, P.

Originální název

DiariZen

Anglický název

DiariZen

Druh

Software

Abstrakt

DiariZen is a cutting-edge speaker diarization toolkit developed by BUT Speech@FIT, combining end-to-end neural diarization (EEND) based on WavLM and Conformer with VBx clustering for accurate and scalable “who spoke when” analysis. Built on the Pyannote framework, it offers modularity, reproducibility, and seamless integration into speech processing pipelines. Structured pruning ensures efficiency without sacrificing performance.

Abstrakt anglicky

DiariZen is a cutting-edge speaker diarization toolkit developed by BUT Speech@FIT, combining end-to-end neural diarization (EEND) based on WavLM and Conformer with VBx clustering for accurate and scalable “who spoke when” analysis. Built on the Pyannote framework, it offers modularity, reproducibility, and seamless integration into speech processing pipelines. Structured pruning ensures efficiency without sacrificing performance.

Klíčová slova

speech recognition, speaker, diarization, toolkit, clustering

Klíčová slova anglicky

speech recognition, speaker, diarization, toolkit, clustering

Licenční poplatek

K využití výsledku jiným subjektem je vždy nutné nabytí licence

www

https://github.com/BUTSpeechFIT/DiariZen