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Combination of CNN and RNN for speech emotion recognition
Vo, TH, Yeom, S 
ORCID: 0000-0002-5843-101X, Na, IS, Oh, A, Lee, GS, Yang, HJ and Kim, SH 2019
, 'Combination of CNN and RNN for speech emotion recognition', in
SMA2019 - The International Conference on Smart Media & Applications
, Smart Media - Korean Institute of Smart Media, South Korea, 163 -166
.
ORCID: 0000-0002-5843-101X, Na, IS, Oh, A, Lee, GS, Yang, HJ and Kim, SH 2019
, 'Combination of CNN and RNN for speech emotion recognition', in
SMA2019 - The International Conference on Smart Media & Applications
, Smart Media - Korean Institute of Smart Media, South Korea, 163 -166
.
Full text not available from this repository.
Official URL: https://kism.jams.or.kr/co/com/EgovMenu.kci?s_url=...
Abstract
Speech Emotion Recognition has several potential applications in health care and human-computer interaction. In recent years, some studies use deep learning to deal with this task, but most of them use shallow neural networks due to the overfitting problem. We proposed an architecture that combines CNN and RNN to learn not only to capture the spatial but also the time-series information. The experiments on VGG-16 and ResNet-101 like networks gave a compatible result with some recent studies.
| Item Type: | Conference Publication |
|---|---|
| Authors/Creators: | Vo, TH and Yeom, S and Na, IS and Oh, A and Lee, GS and Yang, HJ and Kim, SH |
| Keywords: | emotion, speech, human computer interaction, RNN, CNN, Deep learning |
| Journal or Publication Title: | SMA2019 - The International Conference on Smart Media & Applications |
| Publisher: | Smart Media - Korean Institute of Smart Media |
| ISSN: | 2287-4348 |
| Copyright Information: | Copyright unknown |
| Related URLs: | |
| Item Statistics: | View statistics for this item |
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