Speaker Adaptation for Mandarin Syllable Recognition Based on Semi-Continuous Density HMM

• Main Authors: Chien-Hung Chen, 陳健宏
• Other Authors: Chi-Min Liu
• Format: Others
• Language: zh-TW
• Published: 1995
• Online Access: http://ndltd.ncl.edu.tw/handle/66731320553819607466

碩士 === 國立交通大學 === 資訊工程研究所 === 83 === A speaker-dependent speech recognition system performs high recognition rate, but it needs a lot of speaker-specific training data. A speaker-independent (or multi-speaker) system needs no training data from speakers, and it cannot get satis- -factory performance usually. A speaker-adaptive system uses the existing knowledge from a reliably trained reference system, so that a small amount of new speaker's training data is suffi- cient to reach the performance of speaker-dependent system. In this thesis, we consider the applying of speaker adaptation techniques in Mandarin speech. The vocabulary we study has 76 syllables, which include 19 INITIALs and 4 FINALs from the confusing sets in Mandarin syllables. For the reference systems in speaker adaptation, we create speaker-dependent and speaker- independent systems based on the semi-continuous density hidden Markov model (SCHMM). The speaker-dependent system has an aver- -age recognition rate 90.46% and the speaker-independent system 58.97%. On the basis of the two reference systems, we study the Bayesian adaptation techniques with the forward-backward training procedure. We apply the adaptation techniques to adjust codebooks, mixture weights, and transition probabilities in SCHMM. Experiment results show that the adaptation procedure achieves better performance than that of the speaker-independent system with only one training token, it raises recognition rate from 58.97% to 76.65 %. When 3 training tokens are used, the recognition rate approximates that of the speaker-dependent system. When using 6 training tokens, the recognition rate achieves better than that of the speaker-dependent system.