| Autor: |
You-jun LI, Jia-jin HUANG, Hai-yuan WANG, Ning ZHONG |
| Jazyk: |
čínština |
| Rok vydání: |
2017 |
| Předmět: |
|
| Zdroj: |
Tongxin xuebao, Vol 38, Pp 109-120 (2017) |
| Druh dokumentu: |
article |
| ISSN: |
1000-436X |
| DOI: |
10.11959/j.issn.1000-436x.2017294 |
| Popis: |
In order to achieve more accurate emotion recognition accuracy from multi-modal bio-signal features，a novel method to extract and fuse the signal with the stacked auto-encoder and LSTM recurrent neural networks was proposed.The stacked auto-encoder neural network was used to compress and fuse the features.The deep LSTM recurrent neural network was employed to classify the emotion states.The results present that the fused multi-modal features provide more useful information than single-modal features.The deep LSTM recurrent neural network achieves more accurate emotion classification results than other method.The highest accuracy rate is 0.792 6 |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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