Human-computer Interaction Speech Emotion Recognition Based on Random Forest and Convolution Feature Learning

doi:10.16182/j.issn1004731x.joss.20-FZ0494E

Abstract

Abstract: Focus on the different speech features of different types of people in the automatic speech emotion recognition of emotional robots,a random forest for speech emotion recognition is proposed,and a preliminary simulation experiment of emotional social robot system based on convolution feature learning is carried out.The results show that the emotional robot can track in real time,the seven basic emotions of excitement,anger,sadness,happiness,surprise,fear and neutrality.By using non personalized speech emotion features,the original personalized speech emotion features are supplemented,and the general emotion and special emotion are extracted.For emotional robot,using these indicators has a certain application prospect in the simulation experiment and application experiment.

Key words: emotional robot, automatic speech emotion recognition, random forest, convolution feature learning

CLC Number:

TP391.9

Wang Jing, Liu Hongyan, Liu Fangfang, Wang Qingqing. Human-computer Interaction Speech Emotion Recognition Based on Random Forest and Convolution Feature Learning[J]. Journal of System Simulation, 2020, 32(12): 2388-2400.

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