3D Convolutional Recurrent Global Neural Network for Speech Emotion Recognition

被引：6
|
作者：
Zayene, Baraa
Jlassi, Chiraz
Arous, Najet
机构：
来源：
2020 5TH INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES FOR SIGNAL AND IMAGE PROCESSING (ATSIP'2020) | 2020年
关键词：
speech emotion recognition; convolutional neural networks; recurrent neural networks; log-mels;
D O I：
10.1109/atsip49331.2020.9231597
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Nowadays emotion recognition has become the most interesting topic due its important role in Human Computer Interaction (HCI). Speech emotion recognition is a part of this topic which is gaining more popularity in the last years. To recognize emotion, many methods have been developed using machine learning. In this work, we use a deep neural network which takes as input personalized features. To test our proposed system we used several databases with different languages to train and to evaluate our model.
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收藏
页数：5
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