Combination of Fourier and wavelet transformations for detection of speech emotions

M. Ziólko, Pawel Jaciów, M. Igras
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引用次数: 6

Abstract

The paper presents an approach to automatic recognition of emotions in speech signals. The applied method bases on the composition of two discrete frequency transformations. The wavelet transform was calculated first and next the Fourier transform was applied. The Fourier-wavelet transform representation is used to find the differences between emotions in speech signals. A set of approximately 30 seconds long speech signals was used to verify the efficiency of presented methods. It gives the possibility of analyzing the performance of speech emotion recognition in the Fourier-wavelet domain.
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结合傅里叶变换和小波变换检测语音情绪
提出了一种语音信号中情绪的自动识别方法。应用的方法基于两个离散频率变换的复合。首先计算小波变换,然后进行傅里叶变换。采用傅里叶-小波变换表示来寻找语音信号中情绪之间的差异。用一组约30秒长的语音信号验证了所提方法的有效性。这为在傅里叶-小波域分析语音情感识别的性能提供了可能性。
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