Speech Emotion Recognition Using Deep Learning Techniques: A Review

IEEE Access

Thamer Alhussain¹  Tariqullah Jan²  Mohammad Inayatullah Babar²  Ruhul Amin Khalil²  Edward Jones³  Mohammad Haseeb Zafar⁴ 

[1] Department of E-Commerce, Saudi Electronic University (SEU), Riyadh, Saudi Arabia;Department of Electrical Engineering, Faculty of Electrical and Computer Engineering, University of Engineering and Technology, Peshawar, Pakistan;Department of Electrical and Electronics Engineering, National University of Ireland, Galway, Ireland;Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia;

关键词: Speech emotion recognition;    deep learning;    deep neural network;    deep Boltzmann machine;    recurrent neural network;    deep belief network;   

DOI  :  10.1109/ACCESS.2019.2936124

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown