Deep Learning for Enhanced Speech Communication: Integrating Real-time Voice Command Recognition and Emotion Analysis

Rabbani, Saif Shuhab (2023) Deep Learning for Enhanced Speech Communication: Integrating Real-time Voice Command Recognition and Emotion Analysis. Masters thesis, Dublin, National College of Ireland.

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Abstract

This research tackles improved verbal communication via deep learning. It zeroes in on recognizing voice commands and emotion analysis in real-time. We use these tools: voice command recognition, emotion analysis of speech, text classification, and processing speech in multiple ways. This sets the foundation for future communication systems. To pick up voice commands accurately and quickly, neural networks collect data. They track changes in voice command recognition over time. We manage text classification using natural language processing algorithms. These combine text inputs with spoken commands, making the system more flexible. In our thesis, we merge audio-visual data from two sources, sounds and language data. We then apply deep neural networks to understand emotions in speech. We weave these features into one system and It uses different skills to fully understand what the user is communicating. Real-time processing paves the way for swift responses, It makes conversations between users and devices feel natural. Our research produced impressive results like better voice command recognition, improved emotion analysis, and more flexible text classification with accuracy of models ranging from 70% to 88% approximately. The impacts of our work are enormous as research touches areas like human-computer interaction, assistive technologies, and smart environments. This study gives a boost to deep learning in voice processing and helps to create more realistic chats between humans and machines.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Milosavljevic, Vladimir UNSPECIFIED
Uncontrolled Keywords:	Deep Learning; Verbal Communication; Voice Command Recognition; Real-time Processing; Emotion Analysis; Text Classification; Natural Language Processing; Audio-Visual Data
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science H Social Sciences > HM Sociology > Information Science > Communication P Language and Literature > P Philology. Linguistics > Computational linguistics. Natural language processing Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	20 May 2025 16:42
Last Modified:	20 May 2025 16:42
URI:	https://norma.ncirl.ie/id/eprint/7596

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