Application of Teager Energy Operator on Linear and Mel Scales for Whispered Speech Recognition

被引：4
|
作者：
Markovic, Branko R. [1 ]
Galic, Jovan [1 ]
Mijic, Miomir [1 ]
机构：
[1] Sch Elect Engn, Dept Acoust, Blvd Kralja Aleksandra 73, Belgrade 11000, Serbia
来源：
ARCHIVES OF ACOUSTICS | 2018年 / 43卷 / 01期
关键词：
Teager energy operator; cepstral mean subtraction; whispered speech recognition; linear scale; mel scale; dynamic time warping; hidden Markov models;
D O I：
10.24425/118075
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
This paper presents experimental results on whispered speech recognition based on Teager Energy Operator for linear and mel cepstral coefficients including the Cepstral Mean Subtraction normalization technique. The feature vectors taken into consideration are Linear Frequency Cepstral Coefficients, Teager Energy based Linear Frequency Cepstral Coefficients, Mel Frequency Cepstral Coefficients and Teager Energy based Mel Frequency Cepstral Coefficients. A speaker dependent scenario is used. For the recognition process, Dynamic Time Warping and Hidden Markov Models methods are applied. Results show a respectable improvement in whispered speech recognition as achieved by using the Teager Energy Operator with Cepstral Mean Subtraction.
引用
收藏
页码：3 / 9
页数：7
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