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Trends in speech emotion recognition: a comprehensive survey

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Abstract

Among the other modes of communication, such as text, body language, facial expressions, and so on, human beings employ speech as the most common. It contains a great deal of information, including the speaker’s feelings. Detecting the speaker’s emotions from his or her speech has shown to be quite useful in a variety of real-world applications. The dataset development, feature extraction, feature selection/dimensionality reduction, and classification are the four primary processes in the Speech Emotion Recognition process. In this context, more than 70 studies are thoroughly examined in terms of their databases, emotions, features extracted, and classifiers employed. The databases, characteristics, extraction and classification methods, as well as the results, are all thoroughly examined. The study also includes a comparative analysis of these research papers.

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We would like to thank IKG Punjab Technical University, Kapurthala, Punjab (India) for providing the opportunity to carry out the research work.

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    Kamaldeep Kaur

  2. Department of Computer Science & Engineering, Guru Nanak Dev Engineering College, Ludhiana, Punjab, India

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Kaur, K., Singh, P. Trends in speech emotion recognition: a comprehensive survey. Multimed Tools Appl 82, 29307–29351 (2023). https://doi.org/10.1007/s11042-023-14656-y

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