Advance Speech Emotion Recognition using Fuzzy-Based CNN with  Optimal Feature Selection using Beluga Whale Optimization

Chandupatla Deepika,Dr. K. Swarna ,Dr. Shaik Abdul Nabi

Advance Speech Emotion Recognition using Fuzzy-Based CNN with Optimal Feature Selection using Beluga Whale Optimization

Authors

Chandupatla Deepika,Dr. K. Swarna ,Dr. Shaik Abdul Nabi

Keywords:

Speech emotion recognition, Fuzzy neural networks, Convolutional neural networks, Beluga whale optimization, Feature selection, MFCC, Deep learning

Abstract

This research proposes a Speech Emotion Recognition (SER) system that uses a Fuzzy-basedConvolutional Neural Network (CNN) and the Beluga Whale Optimization (BWO) algorithm foroptimal feature selection. The goal is to improve the accuracy of emotion detection from speech by using the BWO

References

Akçay, M.B. and Oğuz, K. (2020) 'Speech emotion recognition: Emotional models, databases, features, preprocessing methods, supporting modalities, and classifiers', Speech Communication, 116, pp. 56-76.

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Published

2024-08-15

How to Cite

Chandupatla Deepika,Dr. K. Swarna ,Dr. Shaik Abdul Nabi. (2024). Advance Speech Emotion Recognition using Fuzzy-Based CNN with Optimal Feature Selection using Beluga Whale Optimization . Journal of Computational Analysis and Applications (JoCAAA), 33(08), 2229–2250. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4272