Speaker Diarization: A Top-Down Approach Using Syllabic Phonology

Abstract

A top-down approach to speaker diarization is developed using a modified Baum-Welch algorithm. The HMM states combine phonemes according to structural positions under syllabic phonological theory. By nature of the structural phonology, there are at most 16 states, and the transition matrix is sparse, allowing efficient decoding to structural phones. This addresses the issue of phoneme specificity in speaker diarization – that speaker similarities/differences are confounded by phonetic similarities/differences. We address this here without the expensive use of a complete set of individual phonemes. The voice activity detection (VAD) issue is likewise addressed, giving a new approach to VAD.