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.
引用
收藏
页数：5
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