Decision tree based Mandarin tone model and its application to speech recognition

Abstract

Tone is an essential language phenomenon for Mandarin Chinese language. Until now, we still do not know exactly how context affects tone pattern variation in continuous Mandarin speech. In this paper, we proposed a decision tree based approach to obtain the quantitative result of tone pattern variation in continuous Mandarin speech. Many possible factors other than tone of neighboring syllables were taken into consideration when the decision tree was constructed, After the tree was established, 29 tone patterns were automatically obtained, and we found that syllable position in the word together with consonant/vowel type of the syllable made an important contribution to tone pattern variation in continuous utterance. We also presented a novel approach to integrate tone information into the search process at word level. Experimental results showed that the character error rate was reduced by 15.2%.