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Empirical mode decomposition based weighted frequency feature for speech-based emotion classification

机译:基于语音的情感分类的实证模式基于加权频率特征

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This paper focuses on speech based emotion classification utilizing acoustic data. The most commonly used acoustic features are pitch and energy, along with prosodic information like rate of speech. We propose the use of a novel feature based on instantan
机译:本文侧重于利用声学数据的基于言语情感分类。最常用的声学特征是音高和能量,以及韵律信息,如语音率。我们建议使用基于instantan的新功能

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