David Palzer

Improving Neural Diarization through Speaker Attribute Attractors and Local Dependency Modeling

In recent years, end-to-end approaches have made notable progress in addressing the challenge of speaker diarization, which involves segmenting and identifying speakers in multi-talker recordings. One such approach, Encoder-Decoder Attractors (EDA), has been proposed to handle variable speaker count…