用于语音情感识别的三维卷积递归全局神经网络

Baraa Zayene, Chiraz Jlassi, N. Arous
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引用次数: 9

摘要

情感识别由于其在人机交互(HCI)中的重要作用而成为当前研究的热点。语音情感识别是这一课题的一部分,近年来越来越受欢迎。为了识别情绪,已经开发了许多使用机器学习的方法。在这项工作中,我们使用深度神经网络作为输入个性化特征。为了测试我们提出的系统,我们使用了几个不同语言的数据库来训练和评估我们的模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
3D Convolutional Recurrent Global Neural Network for Speech Emotion Recognition
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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