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.
Original language | English |
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Article number | 8805181 |
Pages (from-to) | 117327-117345 |
Number of pages | 19 |
Journal | IEEE Access |
Volume | 7 |
DOIs | |
Publication status | Published - 19 Aug 2019 |
Externally published | Yes |
Keywords
- Speech emotion recognition
- convolutional neural network
- deep Boltzmann machine
- deep belief network
- deep learning
- deep neural network
- recurrent neural network