Pretraining an encoder to identify multiple speakers from fully overlapped mixtures yields accurate local diarization without simulated conversational data.
Dataset Table 1 lists the datasets used in our experiments, all monaural with a 16 kHz sampling rate and 16 bit depth
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Pretraining Multi-Speaker Identification for Neural Speaker Diarization
Pretraining an encoder to identify multiple speakers from fully overlapped mixtures yields accurate local diarization without simulated conversational data.