Mispronunciation detection based on cross-language phonological comparisons

Abstract

This paper presents a method using speech recognition with linguistic constraints to detect the mispronunciations made by Cantonese learners of English. The predicted pronunciation errors have been derived from cross-language phonological comparisons, which are used to generate the erroneous pronunciation variations in a lexicon. The acoustic models are trained with native speakers' speech and used for recognizing the phone sequences, given the orthographic transcriptions. The experiments have examined that the agreement between automatic mispronunciation detection and human judges is over 84% for 21 Cantonese speakers.