Speech Emotion Recognition Using Non-Linear Teager Energy Based Features in Noisy Environments

被引：0

作者：

Georgogiannis, Alexandros ^{[1
]}

Digalakis, Vassilis ^{[1
]}

机构：

[1] Tech Univ Crete, Dept Elect & Comp Engn, Khania 73100, Greece

来源：

2012 PROCEEDINGS OF THE 20TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO) | 2012年

关键词：

emotion recognition; speech analysis; nonlinear acoustics;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this study, Teager-energy based Mel-frequency cepstral coefficients (TEMFCCs) are proposed for Automatic Speech Emotion Recognition (ASER) in noisy environments. TEMFCCs are obtained by taking the absolute value of the Teager-energy operator (TEO) of the short-time Fourier transform of the signal (STFT), warping it to a Mel-frequency scale, and taking the discrete cosine transform (DCT) of the log-Mel Teager-energy spectrum. Experiments on classification of discrete emotion categories show that TEMFCCs are more robust than MFCCs in noisy conditions, while TEMFCCs and MFCCs perform similarly for clean conditions.

引用

页码：2045 / 2049

页数：5

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