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

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,...

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Bibliographic Details
Main Authors: Branko R MARKOVIĆ, Jovan GALIĆ, Miomir MIJIĆ
Format: Article
Language:English
Published: Institute of Fundamental Technological Research Polish Academy of Sciences 2018-01-01
Series:Archives of Acoustics
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Online Access:https://acoustics.ippt.pan.pl/index.php/aa/article/view/1996
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Summary: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.
ISSN:0137-5075
2300-262X