Mohammad Amaz Uddin1, Mohammad Salah Uddin Chowdury1, Mayeen Uddin Khandaker2,*, Nissren Tamam3, Abdelmoneim Sulieman4
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1709-1722, 2023, DOI:10.32604/cmc.2023.031177
Abstract Human speech indirectly represents the mental state or emotion of others. The use of Artificial Intelligence (AI)-based techniques may bring revolution in this modern era by recognizing emotion from speech. In this study, we introduced a robust method for emotion recognition from human speech using a well-performed preprocessing technique together with the deep learning-based mixed model consisting of Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN). About 2800 audio files were extracted from the Toronto emotional speech set (TESS) database for this study. A high pass and Savitzky Golay Filter have been used to obtain noise-free as well as… More >
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