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Speech Emotion Recognition With Osmotic Computing
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Author(s): T. Manoj Praphakar (Sri Shakthi Institute of Engineering and Technology, India), D. S. Dhenu (Sri Shakthi Institute of Engineering and Technology, India), D. Gavash (Sri Shakthi Institute of Engineering and Technology, India), M. Mega Shree (Sri Shakthi Institute of Engineering and Technology, India)and S. Divesh (Sri Shakthi Institute of Engineering and Technology, India)
Copyright: 2024
Pages: 23
Source title:
Advanced Applications in Osmotic Computing
Source Author(s)/Editor(s): G. Revathy (SASTRA University, India)
DOI: 10.4018/979-8-3693-1694-8.ch006
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Abstract
Speech emotion recognition is a critical component of human-computer interaction and affective computing. This chapter presents a comprehensive study on the application of deep learning techniques for the task of speech emotion recognition. Emotions conveyed through speech play a crucial role in understanding human behavior and are essential in various domains, including human-robot interaction, customer service, and mental health assessment. This chapter also investigates the impact of different feature extraction methods and data pre-processing techniques on the recognition accuracy. Basically, RNN algorithm is used for speech emotion recognition to identify the emotion through audio, but this chapter will accomplish this with CNN algorithm because the time complexity of RNN algorithm is high and to analyze the audio takes more time where CNN will be converted into spectrograms from each dimension of emotions, which will be recognized by augmenting it. And finally, it is used in the medical field, security, and surveillance management.
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