Adaptive algorithm for feature selection of speech emotion recognition based on genetic algorithm and SVM

Abstract

As a key carrier for people to obtain information in daily life, speech not only provides text signals, but also contains emotional signals. As an important factor of semantics, emotion signals are the focus of improving the intelligent level of human-computer interaction. Therefore, it is important to improving the accuracy of speech emotion recognition. This paper proposes to incorporate derivative feature parameters into the voice emotion recognition feature selection, and to improve the feature selection algorithm based on genetic algorithm and SVM. This article may provide technical support to promote the development of artificial intelligence.