Language is an important part of everyday information communication, and automatic speech emotion information recognition technology has broad application prospects in education, services and medicine. The purpose of this paper is to study speech emotion recognition by specific fuzzy support vector machines. The applicability of fuzzy theory for solving speech emotion states is investigated and the theory of support vector machines, fuzzy support vector machines, is introduced to analyse speech emotion feature extraction in terms of both short-time energy and resonance peaks. The performance of SVM and FSVM methods are compared using Emo-DB corpus tests and it is found that the FSVM method has a higher recognition rate than the SVM method.

Hui Ma. Speech Emotion Recognition Based on Fuzzy Support Vector Machine. Machine Learning Theory and Practice (2022), Vol. 3, Issue 4: 44-52. https://doi.org/10.38007/ML.2022.030406.

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