AN IMPROVED ALGORITHM OF GMM VOICE CONVERSION SYSTEM BASED ON CHANGING THE TIME-SCALE  

作　　者：Zhou Ying Zhang Linghua 

机构地区：[1]College of Telecommunications ＆ Information Engineering, Nanjing University of Posts and Telecommunications Nanjing 210003, China

出　　处：《Journal of Electronics(China)》2011年第4期518-523,共6页电子科学学刊（英文版）

基　　金：Supported by the National Natural Science Foundation of China (No. 60872105);the Program for Science & Technology Innovative Research Team of Qing Lan Project in Higher Educational Institutions of Jiangsu;the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)

摘　　要：This paper improves and presents an advanced method of the voice conversion system based on Gaussian Mixture Models(GMM) models by changing the time-scale of speech.The Speech Transformation and Representation using Adaptive Interpolation of weiGHTed spectrum(STRAIGHT) model is adopted to extract the spectrum features,and the GMM models are trained to generate the conversion function.The spectrum features of a source speech will be converted by the conversion function.The time-scale of speech is changed by extracting the converted features and adding to the spectrum.The conversion voice was evaluated by subjective and objective measurements.The results confirm that the transformed speech not only approximates the characteristics of the target speaker,but also more natural and more intelligible.This paper improves and presents an advanced method of the voice conversion system based on Gaussian Mixture Models（GMM） models by changing the time-scale of speech.The Speech Transformation and Representation using Adaptive Interpolation of weiGHTed spectrum（STRAIGHT） model is adopted to extract the spectrum features,and the GMM models are trained to generate the conversion function.The spectrum features of a source speech will be converted by the conversion function.The time-scale of speech is changed by extracting the converted features and adding to the spectrum.The conversion voice was evaluated by subjective and objective measurements.The results confirm that the transformed speech not only approximates the characteristics of the target speaker,but also more natural and more intelligible.

关 键 词：Gaussian Mixture Models(GMM) Speech Transformation and Representation using Adaptive Interpolation of weiGHTed spectrum(STRAIGHT) TIME-SCALE Voice conversion 

分 类 号：TN912.3[电子电信—通信与信息系统]