| 基于神经网络的语音识别系统 |
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| 引用本文： | 刘潇,和应民,陈力伟.基于神经网络的语音识别系统[J].应用科技,2006,33(6):18-20,23. |
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| 作者姓名： | 刘潇 和应民 陈力伟 |
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| 作者单位： | 哈尔滨工程大学,信息与通信工程学院,黑龙江,哈尔滨,150001 |
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| 摘 要： | 介绍一种适用于实时语音识别环境下的神经网络模型——动态识别神经网络（dynamic recognition neural network，DRNN）．DRNN聚类学习的性能使得它非常适用于与在线学习方式相结合的实时语音识别系统．通过比较DRNN和隐含马尔科夫模型（hidden Markov model，HMM），可以看到不论是在训练方面还是在识别方面，DRNN算法的计算复杂程度都要低于HMM算法．
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| 关 键 词： | 语音识别 自适应神经网络 聚类学习 |
| 文章编号： | 1009-671X（2006）06-0018-04 |
| 收稿时间： | 2005-06-06 |
| 修稿时间： | 2005年6月6日 |
A speech recognition system based on neural network |
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| LIU Xiao,HE Ying-min,CHEN Li-wei.A speech recognition system based on neural network[J].Applied Science and Technology,2006,33(6):18-20,23. |
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| Authors: | LIU Xiao HE Ying-min CHEN Li-wei |
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| Abstract: | A neural network model,dynamic recognition neural network(DRNN),is presented for real-time speech recognition.The property of clustering learning of the DRNN makes it very suitable for real-time speech recognition with on-line learning ability.A comparison between the DRNN and hidden Markov model(HMM) shows that the computational complexity of the former is lower than that of the latter in both training and recognition. |
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| Keywords: | DRNN HMM |
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