Speech emotion recognition using optimized genetic algorithm-extreme learning machine

Automatic Emotion Speech Recognition (ESR) is considered as an active research field in the Human-Computer Interface (HCI). Typically, the ESR system is consisting of two main parts: Front-End (features extraction) and Back-End (classification). However, most previous ESR systems have been focused o...

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Vydané v:	Multimedia tools and applications Ročník 81; číslo 17; s. 23963 - 23989
Hlavní autori:	Albadr, Musatafa Abbas Abbood, Tiun, Sabrina, Ayob, Masri, AL-Dhief, Fahad Taha, Omar, Khairuddin, Maen, Mhd Khaled
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.07.2022 Springer Nature B.V
Predmet:	Accuracy Artificial neural networks Boredom Classification Computer Communication Networks Computer Science Data Structures and Information Theory Emotion recognition Emotion speech recognition Emotions Feature extraction Females Genetic algorithms Human-computer interface Machine learning Males Mel frequency cepstral coefficients Multimedia Information Systems Optimized genetic algorithm-extreme learning machine Special Purpose and Application-Based Systems Speech recognition Optimized genetic algorithm-extreme learning machine Emotion speech recognition Mel frequency cepstral coefficients
ISSN:	1380-7501, 1573-7721, 1573-7721
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