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Combination of Fourier and wavelet transformations for detection of speech emotions

机译:傅里叶变换与小波变换相结合的语音情感检测

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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.
机译:本文提出了一种自动识别语音信号中的情绪的方法。应用的方法基于两个离散频率变换的组合。首先计算小波变换,然后应用傅立叶变换。傅立叶小波变换表示法用于发现语音信号中情绪之间的差异。使用一组大约30秒长的语音信号来验证所提出方法的效率。它提供了分析语音情感识别在傅立叶小波域中的性能的可能性。

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