Augmented audio data in improving speech emotion classification tasks

Nusrat J. Shoumy, Li Minn Ang, D. M.Motiur Rahaman, Tanveer Zia, Kah Phooi Seng, Sabira Khatun

Research output: Book chapter/Published conference paperConference paperpeer-review

Abstract

To achieve high performance and classification accuracy, classification of emotions from audio or speech signals requires large quantities of data. Big datasets, however, are not always readily accessible. A good solution to this issue is to increase the data and augment it to construct a larger dataset for the classifier’s training. This paper proposes a unimodal approach that focuses on two main concepts: (1) augmenting speech signals to generate additional data samples; and (2) constructing classification models to identify emotion expressed through speech. In addition, three classifiers (Convolutional Neural Network (CNN), Naïve Bayes (NB) and K-Nearest Neighbor (kNN)) were further tested in order to decide which of the classifiers had the best results. We used augmented audio data from a dataset (SAVEE) in the proposed method to conduct training (50%), and testing (50%) was executed using the original data. The best performance of approximately 83% was found to be a mixture of augmentation strategies using the CNN classifier. Our proposed augmentation approach together with appropriate classification model enhances the efficiency of voice emotion recognition.

Original languageEnglish
Title of host publicationAdvances and Trends in Artificial Intelligence. From Theory to Practice. IEA/AIE 2021.
EditorsHamido Fujita, Ali Selamat, Jerry Chun-Wei Lin, Moonis Ali
PublisherSpringer
Pages360-365
Number of pages6
ISBN (Electronic)9783030794637
ISBN (Print)9783030794620
DOIs
Publication statusE-pub ahead of print - 19 Jul 2021
Event34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021 - Virtual conference
Duration: 26 Jul 202129 Jul 2021
https://ieaaie2021.wordpress.com/ (Conference website)
https://jsasaki3.wixsite.com/website-4 (Conference schedule)

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12799 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021
Period26/07/2129/07/21
OtherThe 34th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems IEA/AIE 2021 continues the tradition of emphasizing on applications of applied intelligent systems to solve real-life problems in all areas including engineering, science, industry, automation & robotics, business & finance, medicine and biomedicine, bioinformatics, cyberspace, and human-machine.
Internet address

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