Speech Emotion Recognition Using Deep Learning Techniques: A Review
Ruhul Amin Khalila, Edward Jonesb, Mohammad Inayatullah Babara, Tariqullah Jana, Mohammad Haseeb Zafarc, Thamer Alhussaind
- aDepartment of Electrical Engineering, University of Engineering and Technology, Peshawar, Pakistan
- bDepartment of Electrical and Electronics Engineering, National University of Ireland, Galway, Ireland
- cDepartment of Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia
- dDepartment of E-Commerce, Saudi Electronic University (SEU), Riyadh, Saudi Arabia
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Abstract
Emotion recognition from speech signals is an important but challenging component of Human-Computer Interaction (HCI). In the literature of speech emotion recognition (SER), many techniques have been utilized to extract emotions from signals, including many well-established speech analysis and classification techniques. Deep Learning techniques have been recently proposed as an alternative to traditional techniques in SER. This paper presents an overview of Deep Learning techniques and discusses some recent literature where these methods are utilized for speech-based emotion recognition. The review covers databases used, emotions extracted, contributions made toward speech emotion recognition and limitations related to it.
TL;DRAn overview of Deep Learning techniques is presented and some recent literature where these methods are utilized for speech-based emotion recognition is discussed, including databases used, emotions extracted, contributions made toward speech emotion recognition and limitations related to it. (Semantic Scholar)