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Comparative Analysis of Different Classifiers for Speech Emotion Recognition

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Proceedings of International Conference on Advances in Computer Engineering and Communication Systems

Part of the book series: Learning and Analytics in Intelligent Systems ((LAIS,volume 20))

Abstract

Speech Emotion Recognition has been a vital topic of research in human–machine interface applications for many years. It attempts to make human–machine interactions more intelligent by understanding the emotional state of human beings. This paper presents an up-to-date survey of Speech Emotion Recognition discussing the important approaches regarding the use of different classification algorithms to recognize emotions. The focus is mainly on classifiers like Multilayer Perceptron (MLP), Support Vector Machine, Decision Tree, Random Forest, and Convolutional Neural Network (CNN). First, an acted emotional dataset, RAVDESS, will be discussed in detail. Second, the features that were extracted and selected will be addressed. Then, the focus is shifted to these classifier algorithms that categorize the input data into four classes of emotions: happy, angry, sad, and neutral. Each algorithm is implemented and its performance is compared with the others. Finally, conclusions about the best working model and limitations of each classifier used for Speech Emotion Recognition System are presented.

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Authors and Affiliations

  1. CSE, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India

    A. Madhavi, Albert Priya Valentina, Karakavalasa Mounika, Boddeda Rohit & Sheripally Nagma

Authors
  1. A. Madhavi
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  2. Albert Priya Valentina
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  3. Karakavalasa Mounika
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  4. Boddeda Rohit
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  5. Sheripally Nagma
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Corresponding author

Correspondence to Albert Priya Valentina .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, Telangana, India

    C. Kiran Mai

  2. Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, Telangana, India

    B. V. Kiranmayee

  3. Department of Informatics and Computer Techniques, Siberian State Aerospace University of Science and Technology, Krasnoyarsk, Krasnoyarsk Territory, Russia

    Margarita N. Favorskaya

  4. School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, India

    Suresh Chandra Satapathy

  5. CMR Technical Campus, Hyderabad, Telangana, India

    K. Srujan Raju

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Madhavi, A., Priya Valentina, A., Mounika, K., Rohit, B., Nagma, S. (2021). Comparative Analysis of Different Classifiers for Speech Emotion Recognition. In: Kiran Mai, C., Kiranmayee, B.V., Favorskaya, M.N., Chandra Satapathy, S., Raju, K.S. (eds) Proceedings of International Conference on Advances in Computer Engineering and Communication Systems. Learning and Analytics in Intelligent Systems, vol 20. Springer, Singapore. https://doi.org/10.1007/978-981-15-9293-5_48

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  • DOI: https://doi.org/10.1007/978-981-15-9293-5_48

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-9292-8

  • Online ISBN: 978-981-15-9293-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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