Continuous Audiovisual Emotion Recognition Using Feature Selection and LSTM

Speech and visual information are the most dominant modalities for a human to perceive emotion. A method of recognizing human emotion from these modalities is proposed by utilizing feature selection and long short-term memory (LSTM) neural networks. A feature selection method based on support vector...

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Veröffentlicht in:	Journal of Signal Processing 2020/11/01, Vol.24(6), pp.229-235
Hauptverfasser:	Elbarougy, Reda, Atmaja, Bagus Tris, Akagi, Masato
Format:	Artikel
Sprache:	eng
Schlagworte:	Arousal audiovisual continuous emotion recognition Correlation coefficients Emotion recognition Emotions Feature recognition feature selection LSTM Neural networks Speech recognition Support vector machines
Online-Zugang:	Volltext
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