Identification of accent and intonation in sentences for CALL systems

Abstract

In order to construct a CALL (Computer Aided Language Learning) system that can teach learners accent and intonation of Japanese, it's necessary to automatically identify accent types and intonation types in sentence utterances. For this purpose, several acoustic (prosodic) features of speech were investigated taking their effects on human perception into account. For the accent type identification method, the use of average values of F0 in mora and target values of F0 in mora final was evaluated in CV and VC units. Average values of VC units and target values of CV units showed better performance in the identification task. As for the intonation identification, several acoustic features were investigated to represent 6 types of sentence final tones, each conveying different information of intention and perceptual impression. The proposed acoustic features for relative duration and sentence final pitch change showed good correspondence to perceptual features.