An ongoing review of speech emotion recognition

•We introduce the field of speech emotion recognition.•We review most popular datasets for validation.•We review current machine learning and neural networks models for SER. User emotional status recognition is becoming a key feature in advanced Human Computer Interfaces (HCI). A key source of emoti...

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Bibliographic Details
Published in:Neurocomputing (Amsterdam) 2023-04, Vol.528, p.1-11
Main Authors: de Lope, Javier, Graña, Manuel
Format: Article
Language:English
Subjects:
Datasets
Deep learning
Machine learning
Speech emotion recognition
Speech feature extraction
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Summary:•We introduce the field of speech emotion recognition.•We review most popular datasets for validation.•We review current machine learning and neural networks models for SER. User emotional status recognition is becoming a key feature in advanced Human Computer Interfaces (HCI). A key source of emotional information is the spoken expression, which may be part of the interaction between the human and the machine. Speech emotion recognition (SER) is a very active area of research that involves the application of current machine learning and neural networks tools. This ongoing review covers recent and classical approaches to SER reported in the literature.
ISSN:0925-2312
1872-8286
DOI:10.1016/j.neucom.2023.01.002