A New Method for Noisy Speech Classification Based on Gaussian Mixture Models
Speech can be broadly categorized into voiceless,voiced,and mute signal,in which voiced speech can be further classified into vowel and voiced consonant.With the ever increasing demand of the speech synthesis applications,it is urgent to develop an effective classification method to differentiate vowel and voiced consonant signal since they are two distinct components that affect the naturalness of the synthetic speech signal.State-of-the-arts algorithms for speech signal classification are effective in classifying voiceless,voiced and mute speech signal,however,not effective in further classifying the voiced signal.In view of the issue,a new algorithm for speech classification based on Gaussian Mixture Model (GMM) is proposed,which can directly classify a speech into voiceless,voiced consonant,vowel and mute signal.Specifically,a new speech feature is proposed,and the GMM is also modified for speech classification.Simulation results demonstrate that the proposed algorithm is effective even under the noisy environments.
noisy speech signal energy distribution Gaussian mixture model
Lihai Yao Jie Xu Hao Jiang
School of Information and Electrical Engineering Zhejiang University City CollegeHangzhou, Zhejiang Province 310015, China
国际会议
西安
英文
1253-1257
2012-08-24（万方平台首次上网日期，不代表论文的发表时间）