Robust Speech Recognition Using Noise-Cluster HMM Interpolation

摘要：

This paper proposes a novel approach called noisecluster HMM interpolation for robust speech recognition.The approach helps alleviating the problem of speech recognition under noisy environments not trained in the system.In this method,a new HMM is interpolated from existing noisy-speech HMMs that are best matched to the input speech.This process is performed on-the-fly with an acceptable delay time and,hence,no need to prepare and store the final model in advance.Interpolation weights among HMMs can be determined by either a direct or a tree-structured search.Evaluated focusing on speech in unseen noisy-environments,the proposed method obviously outperforms a baseline system whose acoustic model for such unseen environment is selected from a tree structure.

作者: Nattanun Thatphithakkul Boontee Kruatrachue Chai Wutiwiwatchai Sanparith Marukatat Vataya Boonpiam

作者单位: Computer Engineering Department,Faculty of Engineering,King Mongkuts Institute of Technology Ladkra Computer Engineering Department,Faculty of Engineering,King Mongkuts Institute of Technology Ladkra Speech Technology Section,Human Language Technology Laboratory National Electronics and Computer Tec Speech Technology Section,Human Language Technology Laboratory National Electronics and Computer Tec

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）