[1]韩志艳,伦淑娴,王健.基于遗传小波神经网络的语音情感识别[J].计算机技术与发展,2013,(01):75-78.
　HAN Zhi-yan,LUN Shu-xian,WANG Jian.Speech Emotion Recognition Based on Genetic Wavelet Neural Network[J].,2013,(01):75-78.
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基于遗传小波神经网络的语音情感识别()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2013年01期
页码:
75-78
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
Speech Emotion Recognition Based on Genetic Wavelet Neural Network
文章编号:
1673-629X（2013）01-0075-04
作者:
韩志艳; 伦淑娴; 王健
渤海大学 工学院
Author(s):
HAN Zhi-yan; LUN Shu-xian; WANG Jian
关键词:
情感识别; 神经网络; 遗传算法; 小波分析
Keywords:
emotion recognition; neural network; genetic algorithm; wavelet transform
文献标志码:
A
摘要:
情感识别是人机交互领域中必须解决的关键问题.针对语音情感的识别问题,文中把遗传算法和小波神经网络算法相结合,即利用遗传算法具有的高度并行、随机、自适应搜索性能来选取初值进行训练,用小波神经网络来完成给定精度的学习.这样在解决复杂和非线性问题时,具有明显的优势.文中主要研究了四种基本的人类情感:喜悦、愤怒、悲伤和恐惧.并与 BP 算法和小波神经网络算法进行了比较,实验结果表明,该模型不但能够提高情感识别的正确率,缩短系统识别时间,而且为算法的实用性奠定了基础
Abstract:
Emotion recognition is the key issue that must be solved in human-computer interaction. Aiming at the recognition problem of speech emotion,combined genetic algorithm and wavelet neural network algorithm,utilize the performance of height parallel,random and adaptive search to select initial values,and using wavelet neural network to finish the learning. This has obvious advantages of solving complex and nonlinear problem. Four basic human emotions including joy,anger,sadness and fear were studied,and compared with back propagation neural network (BPNN) and wavelet neural network. The experimental results indicate that this method effectively improves the correct rate of emotion recognition,shortens the system recognition time,and lays the foundation for algorithm practicality

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更新日期/Last Update: 1900-01-01