[1]余华,黄程韦,张潇丹,等.混合蛙跳算法神经网络及其在语音情感识别中的应用[J].南京理工大学学报(自然科学版),2011,(05):659-663.
 YU Hua,HUANG Cheng-wei,ZHANG Xiao-dan,et al.Shuffled Frog-leaping Algorithm Based Neural Network and Its Application in Speech Emotion Recognition[J].Journal of Nanjing University of Science and Technology,2011,(05):659-663.
点击复制

混合蛙跳算法神经网络及其在语音情感识别中的应用
分享到:

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
期数:
2011年05期
页码:
659-663
栏目:
出版日期:
2011-10-31

文章信息/Info

Title:
Shuffled Frog-leaping Algorithm Based Neural Network and Its Application in Speech Emotion Recognition
作者:
余华12黄程韦1张潇丹1金赟1赵力1
1. 东南大学水声信号处理教育部重点实验室,江苏南京210096; 2. 南京信息职业技术学院电子信息学院,江苏南京210013
Author(s):
YU Hua12 HUANG Cheng-wei1ZHANG Xiao-dan1 JIN Yun1ZHAO Li1
1. Key Laboratory of Underwater Acoustic Signal Processing of Ministry of Education,Southeast University, Nanjing 210096,China; 2. School of Electronics and Information Engineering,Nanjing College of Information Technology,Nanjing 210013,China
关键词:
混合蛙跳算法 神经网络 语音情感识别 辨识率
Keywords:
shuffled frog-leaping algorithm neural networks speech emotion recognition recognition ratio
分类号:
391. 42
摘要:
该文将混合蛙跳算法( SELA) 优化方法应用于人工神经网络训练中,对6 种语音情感进 行了语音情感特征的分析与识别。研究了谐波噪声比特征随情感类别的变化特性。利用混合 蛙跳算法训练随机产生的初始数据优化神经网络的连接权值,快速实现了网络收敛。实验比较 了BP 神经网络、RBF 神经网络和SFLA 神经网络的语音情感识别性能。结果表明,SFLA 神经 网络的平均识别率分别高于BP 神经网络和RBF 神经网络4. 7%和4. 3%。
Abstract:
The shuffled frog-leaping algorithm( SFLA) is applied to the speech emotion recognition in neural network training. The freatures of the six speech emotions are extracted and recognized. The changes of harmonics-to-noise ratio( HNR) features with different emotions are studied. The random initial data trained by the SFLA is used to optimize the connection weights and thresholds of the neural network,and the network can converge fast. The recognition capability of the BP,RBF and SFLA neural networks are compared experimentally. The results show that the recognition ratio of the SFLA neural network is 4. 7% better than that of BP neural network and 4. 3% better than that of the RBF neural network.

参考文献/References:

[1] Picard R W. Affective Computing[M]. Cambridge: MIT Press, 1997.
[2] Picard R W. Toward computers that recognize and respond to user emotion[J]. IBM Technical Journal, 2000, 38( 2) : 705-719.
[3] 赵力,将春辉,邹采荣,等. 语音信号中的情感特征 分析和识别的研究[J]. 通信学报, 2000, 21( 10) : 18 -25.
[4] 金赟,赵艳,黄程韦,等. 耳语音情感数据库的设计 与建立[J]. 声学技术, 2010, 29( 1) : 63-68.
[5] 袁家斌,浦海晨. 基于遗传算法优化的神经网络电 子邮件信息分类器的研究[J]. 南京理工大学学报, 2008, 32( 1) : 78-82.
[6] 秦华旺,戴跃伟,王执铨. 一种基于改进神经网络的 入侵容忍系统模型[J]. 南京理工大学学报, 2008, 32( 5) : 628-631.
[7] 赵英,催福义,郭亮,等. 基于BP 神经网络的天津于 桥水库CODMn 预测研究[J]. 南京理工大学学报, 2008, 32( 3) : 376-380.
[8] 陈得宝,赵春霞. 基于改进GA 的WRBF 神经网络 设计与应用[J]. 南京理工大学学报,2007,31( 3) : 370-374.
[9] 朱红,陈清华,刘国岁. 高速神经网络HS-K-WTA-2 的研究[J]. 南京理工大学学报2007,31 ( 1 ) : 89 -91.
[10] 何春梅,叶有培,徐蔚鸿. 训练模式对的摄动对单体 模糊神经网络的影响[J]. 南京理工大学学报, 2009, 33( 1) : 12-15.
[11] Eusuff M M,Lansey K E. Shuffled frog-leaping algorithm: A memetic meta-heuristic for discrete optimization[J]. Engineering Optimization,2006,38 ( 2) : 129-154.
[12] Yang Junan,Zhuang Zhenquan. Research of quantum genetic algorithm and its application in blind source separation[J]. Journal of Electronics ( China) ,2003, 20( 1) : 62-68.
[13] 黄程韦,金赟,赵力,等. 基于特征空间分解与融合 的语音情感识别[J]. 信号处理,2010,26 ( 6) : 835 -842.
[14] 黄程韦,金赟,赵艳,等. 实用语音情感数据库的设 计与研究[J]. 声学技术, 2010, 29( 1) : 63-68.
[15] Huang Chengwei, Jin Yun,Zhao Yan, et al. Recognition of practical emotion from elicited speech[A]. Proceedings of ICISE[C]. Nanjing,China: IEEE,2009: 639 -642.
[16] Huang Chengwei, Jin Yun,Zhao Yan,et al. Speech emotion recognition based on re-composition of two-class classifiers[A]. Proceedings of ACII[C]. Amsterdam, Netherland: IEEE, 2009: 1-3.
[17] Tato R,Santos R,Kompe R,et al. Emotion space improves emotion recognition[A]. Proc of ICSLP[C]. Denver,Colorado IEEE, 2009: 2029-2032.
[18] Eiji Yumoto,Wilbur J G. Harmonics-to-noise ratio as an index of the degree of hoarseness[J]. Journal of Acoustic Society of America, 1982, 71( 6) : 1544-1550.

相似文献/References:

[1]陈机林,王力,高强,等.爆破扫雷器电液伺服系统建模[J].南京理工大学学报(自然科学版),2012,36(04):645.
 CHEN Ji-lin,WANG Li,GAO Qiang,et al.Modeling of Electro-hydraulic Servo System of Explosive Sweeper Mine Device[J].Journal of Nanjing University of Science and Technology,2012,36(05):645.
[2]高强,金勇,侯远龙,等.某扫雷车扫雷犁电液伺服系统辨识与控制[J].南京理工大学学报(自然科学版),2012,36(02):238.
 GAO Qiang,JIN Yong,HOU Yuan-long,et al.Modeling and Control for Mine Sweeping Plough Electro-hydraulic Servo System of Certain Mine-clearing Vehicle[J].Journal of Nanjing University of Science and Technology,2012,36(05):238.
[3]林棻,赵又群.汽车侧偏角估计方法比较[J].南京理工大学学报(自然科学版),2009,(01):122.
 LIN Fen,ZHAO You-qun.Comparison of Methods for Estimating Vehicle Side Slip Angle[J].Journal of Nanjing University of Science and Technology,2009,(05):122.
[4]李成国,牟善祥,张忠传,等.基于LTCC的Ka波段无源等效腔体分析与优化设计[J].南京理工大学学报(自然科学版),2009,(03):371.
 LI Cheng-guo,MU Shan-xiang,ZHANG Zhong-chuan.Analysis and Optimal Design of Passive Equivalent Cavity in Ka Wave Band Based on LTCC[J].Journal of Nanjing University of Science and Technology,2009,(05):371.
[5]秦华旺,戴跃伟,王执铨,等.一种基于改进神经网络的入侵容忍系统模型[J].南京理工大学学报(自然科学版),2008,(05):628.
 QIN Hua-wang,DAI Yue-wei,WANG Zhi-quan.Model of Intrusion Tolerant System Based on Improved Neural Networks[J].Journal of Nanjing University of Science and Technology,2008,(05):628.
[6]张潇丹,胡峰,赵力,等.改进的混合蛙跳算法及其应用[J].南京理工大学学报(自然科学版),2012,36(06):0.
 ZHANG Xiao dan,HU Feng,ZHAO Li,et al.Improved Shuffled Frog Leaping Algorithm and Its Application[J].Journal of Nanjing University of Science and Technology,2012,36(05):0.
[7]钱晓东,王正欧.ART2神经网络聚类的改进研究[J].南京理工大学学报(自然科学版),2007,(01):71.
 QIAN Xiao-dong,WANG Zhen-ou.Improvement of Clustering of ART2 Neural Network[J].Journal of Nanjing University of Science and Technology,2007,(05):71.
[8]李千目,戚湧,张宏,等.IIDS的行为特征提取方法研究[J].南京理工大学学报(自然科学版),2004,(02):140.
 LI Qian-mu,QI Yong,ZHANG Hong,et al.Research on Method for Obtaining Action Character Based on IIDS[J].Journal of Nanjing University of Science and Technology,2004,(05):140.
[9]王树亮,王 东,冯 珍,等.基于小波包-神经网络故障诊断系统研究[J].南京理工大学学报(自然科学版),2004,(04):356.
 WANG Shu liang,WANG Dong,FENG Zhen,et al.Study of Fault Diagnosis System Based on Wavelet Packet-neural Network[J].Journal of Nanjing University of Science and Technology,2004,(05):356.
[10]徐晋.基于神经网络专家系统的创业企业信用等级评估研究[J].南京理工大学学报(自然科学版),2004,(06):684.
 XU Jin.Evaluation Index System of the Venture Enterprise’s Credit Level Based on Artificial Neural Network[J].Journal of Nanjing University of Science and Technology,2004,(05):684.

备注/Memo

备注/Memo:
基金项目: 国家自然科学基金( 60472058; 60975017; 51075068) ; 江苏省自然科学基金( BK2008291) 作者简介: 余华( 1963-) ,女,副教授,主要研究方向: 语音信号处理等,E-mail: air1894@ yahoo. com. cn。
更新日期/Last Update: 2012-10-24