Duch, PiotrWiatrowska, IzabelaKapusta, Paweł2023-09-222023-09-222023Duch 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: 10.34658/9788366741928.42978-83-66741-92-8http://hdl.handle.net/11652/4818https://doi.org/10.34658/9788366741928.42Speech 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.enDla wszystkich w zakresie dozwolonego użytkuFair use conditionartificial intelligencespeech emotion recognitionsztuczna inteligencjarozpoznawanie emocji mowyRozdział - monografiaLicencja PŁLUT License10.34658/9788366741928.42