Automatic evaluation and training in English pronunciation

Abstract

SRI is developing a system that uses real time speech recognition to diag nose, evaluate and provide training in spoken English. The paper first describes the methods and results of a study of the feasibility of automati cally grading the performance of Japanese students when reading English aloud. Utterances recorded from Japanese speakers were independently rated by expert listeners. Speech grading software was developed from a speaker independent hidden-Markov-model speech recognition system. The auto matic grading procedure first aligned the speech with a model and then com pared the segments of the speech signal with models of those segments that have been developed from a database of speech from native speakers of English. The evaluation study showed that ratings of speech quality by experts are very reliable and automatic grades correlate well (r > 0.8) with those expert ratings. SRI is now extending this technology and integrating it in a spoken-language training system. This effort involves (1) porting SRI's DECIPHER speech recognition system to a microcomputer platform, and (2) extending the speech-evaluation software to more exactly diagnose a learner's pronuncia tion deficits and lead the learner through an appropriate regimen of exer cises.