Comparison of Neural Networks for Emotion Detection



Document title: Comparison of Neural Networks for Emotion Detection
Journal: Computación y sistemas
Database:
System number: 000560811
ISSN: 1405-5546
Authors: 1
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Institutions: 1Instituto Politécnico Nacional, Centro de Investigación en Computación, México
Year:
Season: Jul-Sep
Volumen: 27
Number: 3
Pages: 653-665
Country: México
Language: Inglés
English abstract This article presents the findings of a bio-inspired audio emotion-detection system and compares its performance with various neural network approaches, namely spiking neural networks, convolutional neural networks, and multilayer perceptrons. The simulation results demonstrate the effectiveness of the proposed approach in accurately detecting audio emotions. Additionally, the detection task can achieve even higher levels of precision by improving the training methods. The research utilizes the EmoDB, SAVEE, and RAVDESS databases.
Keyword: SNN,
DNN,
MLP,
Emotion recognition,
Encoding
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