首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Tone model integration based on discriminative weight training for Putonghua speech recognition
Authors:HUANG Hao  ZHU Jie
Institution:Department of Electronic Engineering, Shanghai Jiaotong University Shanghai 200240
Abstract:A discriminative framework of tone model integration in continuous speech recognition was proposed. The method uses model dependent weights to scale probabilities of the hidden Markov models based on spectral features and tone models based on tonal features.The weights are discriminatively trahined by minimum phone error criterion. Update equation of the model weights based on extended Baum-Welch algorithm is derived. Various schemes of model weight combination are evaluated and a smoothing technique is introduced to make training robust to over fitting. The proposed method is ewluated on tonal syllable output and character output speech recognition tasks. The experimental results show the proposed method has obtained 9.5% and 4.7% relative error reduction than global weight on the two tasks due to a better interpolation of the given models. This proves the effectiveness of discriminative trained model weights for tone model integration.
Keywords:
本文献已被 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号