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100/12/12(一) Discrimination-emphasized Mel-Frequency-Warping for Time-Varying Speaker Recognition 主講人: 鄭 方教授

國立清華大學

資訊工程學系

Department Of Computer Science

 National Tsing Hua University

專題演講

SEMINAR

 

 

主 講 人: 鄭  方教授

SPEAKER 北京清華大學

 

題  目:Discrimination-emphasized Mel-Frequency-Warping for Time-Varying Speaker Recognition

TOPIC  

 

時  間:100年12月12日(一) 下午2:00~3:00

DATE

 

地    點:資電館447室

PLACE

 

                                 連絡人:張智星 教授

 

敬請踴躍參加

 

Abstract:

Performance degradation with time varying is a generally acknowledged phenomenon in speaker recognition and it is widely assumed that speaker models should be updated from time to time to maintain representativeness. However, it is costly, user-unfriendly, and sometimes, perhaps unrealistic, which hinders the technology from practical applications. From a pattern recognition point of view, the time-varying issue in speaker recognition requires such features that are speaker- specific, and as stable as possible across time-varying sessions. Therefore, after searching and analyzing the most stable parts of feature space, a Discrimination-emphasized Mel-frequency- warping method is proposed. In implementation, each frequency band is assigned with a discrimination score, which takes into account both speaker and session information, and Mel- frequency-warping is done in feature extraction to emphasize bands with higher scores. Experimental results show that in the time-varying voiceprint database, this method can not only improve speaker recognition performance with an EER reduction of 19.1%, but also alleviate performance degradation brought by time varying with a reduction of 8.9%.

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