Trends in speech emotion recognition: a comprehensive survey

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.

Automated summary

Among various modes of communication, speech is the most common one used by humans. It carries a wealth of information, including the speaker's emotions, and has found wide applications in real-world scenarios. This study examines over 70 research papers in terms of their databases, emotions, extracted features, and classifiers, providing a comprehensive analysis of the databases, methods for feature extraction and classification, as well as the results.