IMPROVED SYLLABLE-BASED CONTINUOUS MANDARINE SPEECH RECOGNITION USING INTERSYLLABLE BOUNDARY MODELS

Abstract

A novel approach to compensate for the intersyllable coarticulation effect on continuous Mandarin speech recognition by supplementing the syllable HMM models with intersyllable boundary models is proposed. Experimental results show that the syllable recognition errors of a speaker-dependent recognition task are reduced by 24%.