A Convolutional and Recurrent Neural Network-based Approach for Speech Emotion Recognition
Ładowanie...
Data
2023
Tytuł czasopisma
ISSN czasopisma
Tytuł tomu
Wydawca
Wydawnictwo Politechniki Łódzkiej
Lodz University of Technology Press
Lodz University of Technology Press
Abstrakt
Speech emotion recognition (SER) is a crucial aspect of humancomputer
interaction. In this article, we propose a deep learning approach,
using CNN and RNN architectures, for SER using both convolutional and recurrent
neural networks. We evaluated the approach on four audio datasets,
including CREMA-D, RAVDESS, TESS, and EMOVO. Our experiments tested
various feature sets and extraction settings to determine optimal features for
SER. Our results demonstrate that the proposed approach achieves high accuracy
rates and outperforms state-of-the-art algorithms.
Opis
Słowa kluczowe
artificial intelligence, speech emotion recognition, sztuczna inteligencja, rozpoznawanie emocji mowy
Cytowanie
Duch P., Wiatrowska I., Kapusta P., A Convolutional and Recurrent Neural Network-based Approach for Speech Emotion Recognition. W: Progress in Polish Artificial Intelligence Research 4, Wojciechowski A. (Ed.), Lipiński P. (Ed.)., Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023,
s. 267-272, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.42