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A Review of Feature Extraction and Classification Techniques in Speech Recognition

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Abstract

Speech is one of the most fundamental and essential forms of human communication. Humans and computers interact through what is known as a human–computer interface. Speech can be used to communicate with the computer. Speech recognition is utilised not only in mobile devices, but also in embedded systems, modern desktop and laptop computers, operating systems, and browsers. This is beneficial to children, the senior citizens, and people who are blind or have impaired eyesight. This is especially important for physically handicapped individuals who rely only on this medium to interact with computer systems. The field of voice recognition research is becoming more inventive. Researchers are trying to expand the ways in which computers can use human speech. This review article aims to classify methods for translating human speech into a format that computers can understand. Challenges of the current most popular speech recognition systems are analysed and solutions are presented. This review paper is intended to provide a summary for the researchers who are working in speech recognition. Both feature extraction and classification are critical components of a speech recognition system. The focus of this study is to present a review of the literature on feature extraction and classification strategies for speech recognition systems.

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Authors and Affiliations

  1. Computer Science and Engineering, National Institute of Technology Raipur, Raipur, India

    Sonal Yadav

  2. Indian Institute of Information Technology Kota, Kota, India

    Amit Kumar, Ayu Yaduvanshi & Prateek Meena

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  1. Sonal Yadav
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This article is part of the topical collection “Recent Trends on Agents and Artificial Intelligence” guest edited by Jaap van den Herik, Ana Paula Rocha and Luc Steels.

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Yadav, S., Kumar, A., Yaduvanshi, A. et al. A Review of Feature Extraction and Classification Techniques in Speech Recognition. SN COMPUT. SCI. 4, 777 (2023). https://doi.org/10.1007/s42979-023-02158-5

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