Databases, features and classifiers for speech emotion recognition: a review

Speech is an effective medium to express emotions and attitude through language. Finding the emotional content from a speech signal and identify the emotions from the speech utterances is an important task for the researchers. Speech emotion recognition has considered as an important research area o...

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Bibliographic Details
Published inInternational journal of speech technology Vol. 21; no. 1; pp. 93 - 120
Main Authors Swain, Monorama, Routray, Aurobinda, Kabisatpathy, P.
Format Journal Article
LanguageEnglish
Published New York Springer US 01.03.2018
Springer Nature B.V
Subjects
Algorithms
Artificial Intelligence
Classifiers
Emotion recognition
Emotions
Engineering
Feature recognition
Human behavior
Personal communication
Researchers
Signal,Image and Speech Processing
Social Sciences
Speech
Speech recognition
Classifiers
Emotion recognition
Prosodic features
Spectral features
Excitation features
Speech corpus
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Summary:Speech is an effective medium to express emotions and attitude through language. Finding the emotional content from a speech signal and identify the emotions from the speech utterances is an important task for the researchers. Speech emotion recognition has considered as an important research area over the last decade. Many researchers have been attracted due to the automated analysis of human affective behaviour. Therefore a number of systems, algorithms, and classifiers have been developed and outlined for the identification of emotional content of a speech from a person’s speech. In this study, available literature on various databases, different features and classifiers have been taken in to consideration for speech emotion recognition from assorted languages.
ISSN:1381-2416
1572-8110
DOI:10.1007/s10772-018-9491-z