Development of Speech emotion recognition using Deep Neural Network Architecture for children with Autism Spectrum Disorder

Bhagat, Bijalben Prafulchandra (2022) Development of Speech emotion recognition using Deep Neural Network Architecture for children with Autism Spectrum Disorder. Masters thesis, Dublin, National College of Ireland.

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Abstract

Autism spectrum disorder (ASD) is mostly diagnosed in children who find it very difficult to show the human emotion and socialize themselves. In order to help such childrens, our proposed framework utilizes the deep learning architecture for classifying the various emotions from audio data. After several steps of data collection, data processing, model training and evaluation, we have obtained the better results using Deep neural network architecture. Where the existing model was compared with the convolutional neural network and custom model (combined layer of LSTM and Bi-LSTM). The main purpose of this study, is to identify the optimal model for developing a speech emotion recognition system for children with autism specturm disorder in identification of human emotions.

Item Type:	Thesis (Masters)
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science R Medicine > RJ Pediatrics B Philosophy. Psychology. Religion > Psychology > Emotions Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Tamara Malone
Date Deposited:	18 Jan 2023 17:27
Last Modified:	06 Mar 2023 16:31
URI:	https://norma.ncirl.ie/id/eprint/6087

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