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F0, LPC, and MFCC analysis for emotion recognition based on speech
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Orientador(es)
Resumo(s)
In this work, research was done to understand what is needed to build a database to recognise emotions through speech. Some features that can highlight a good success rate for emotion recognition through
speech were investigated. Also studied were some characteristics (symptoms) that can be associated with a specific emotional state. On the other hand, we also studied some features that can be used to identify
some emotional states. A System Emotion Recognition (SER) was built with SVM, and the binary analysis was compared with a multi-category analysis. The binary analysis achieved an accuracy of 87.5% and the
multi-class 42.6%. The parameters Fundamental Frequency-F0, Linear Predictive Coefficients (LPC), and Mel Frequency Cepstral Coeficients (MFCC) were used. The modest accuracy of this work was achieved using only F0, LPC and MFCC features.
Descrição
Palavras-chave
Emotional state Speech SVM
Contexto Educativo
Citação
Teixeira, Felipe L.; Teixeira, João Paulo; Soares, Salviano F.P.; Abreu, J.L.Pio (2022). F0, LPC, and MFCC analysis for emotion recognition based on speech. In Second International Conference, OL2A 2022. Bragança. 1754, p.389-404
Editora
Springer Nature