Deep features-based speech emotion recognition for smart affective services

• Published in: Multimedia tools and applications Vol. 78; no. 5; pp. 5571 - 5589
• Main Authors: Badshah, Abdul Malik, Rahim, Nasir, Ullah, Noor, Ahmad, Jamil, Muhammad, Khan, Lee, Mi Young, Kwon, Soonil, Baik, Sung Wook
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.03.2019; Springer Nature B.V
• Subjects: Artificial neural networks; Coding; Computer Communication Networks; Computer Science; Data Structures and Information Theory; Emotion recognition; Feature extraction; Feature recognition; Kernels; Multimedia Information Systems; Special Purpose and Application-Based Systems; Spectrograms; Speech; Speech recognition; Rectangular kernels; Convolutional neural network; Spectrogram; Speech emotion recognition
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-017-5292-7

Emotion recognition from speech signals is an interesting research with several applications like smart healthcare, autonomous voice response systems, assessing situational seriousness by caller affective state analysis in emergency centers, and other smart affective services. In this paper, we pres...