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SPEECH EMOTION RECOGNITION USING DEEP NEURAL NETWORKS

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dc.contributor.author Mustazhapov, Raiymbek
dc.date.accessioned 2021-07-28T10:13:26Z
dc.date.available 2021-07-28T10:13:26Z
dc.date.issued 2021-07
dc.identifier.citation Mustazhapov, R. (2021). Speech Emotion Recognition using Deep Neural Networks (Unpublished master's thesis). Nazarbayev University, Nur-Sultan, Kazakhstan en_US
dc.identifier.uri http://nur.nu.edu.kz/handle/123456789/5616
dc.description.abstract There is an apparent evolving interest in speech emotion recognition (SER), one of the particular cases of a broader problem of multimedia pattern recognition. SER is considered to possess the capability to enhance the communication efficiency between human and artificial intelligence providing an emotional context to the machine. The field has been developing fast with the emergence and increase in accessibility of deep learning techniques recently. This potential critical benefit and novel techniques have drawn the attention of many specialists in the field and generated a great number of research papers that furnish diverse intricate methods. One of such methods involving various data augmentation techniques has demonstrated high performance in this field. This paper performs an analysis of various simple augmentation methods to attempt to improve existing models. Particularly, this research focuses on state-ofthe- art CNN models for RAVDESS, EMO-DB, and IEMOCAP datasets, and exploits temporal, spatial, and spectral transformations of sound as an underlying method for augmentation. As a result of exploiting simple augmentations, we achieved an increase in performance for IEMOCAP model and positive effects comparable to their complex counterparts for other datasets. en_US
dc.language.iso en en_US
dc.publisher Nazarbayev University School of Engineering and Digital Sciences en_US
dc.rights Attribution-NonCommercial-ShareAlike 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/3.0/us/ *
dc.subject SER en_US
dc.subject speech emotion recognition en_US
dc.subject Deep Neural Networks en_US
dc.subject DNN en_US
dc.subject AI en_US
dc.subject artificial intelligence en_US
dc.subject Type of access: Open Access en_US
dc.title SPEECH EMOTION RECOGNITION USING DEEP NEURAL NETWORKS en_US
dc.type Master's thesis en_US
workflow.import.source science


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