| 基于小波分析的大词汇汉语连续语音识别系统鲁棒性的研究 |
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| 引用本文： | 颜龙,刘刚,郭军.基于小波分析的大词汇汉语连续语音识别系统鲁棒性的研究[J].中文信息学报,2006,20(2):62-67. |
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| 作者姓名： | 颜龙 刘刚 郭军 |
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| 作者单位： | 北京邮电大学信息工程学院 |
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| 基金项目： | 教育部跨世纪优秀人才培养计划;教育部科学技术研究项目 |
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| 摘 要： | 本文提出一种基于小波分析的大词汇汉语连续语音识别的方法,即采用一维小波变换将原始语音信号进行五层小波分解,然后对各层小波系数进行重构,得到五层语音信号,分别对各层语音信号进行训练,得到各层的声学模型,然后结合语言模型对各层声学模型的性能进行测试。通过对纯净语音和带噪语音的各层重构语音数据进行测试。结果表明对于含有高斯白噪声的带噪语音,该方法能使系统性能有所提高,但对于粉红噪声,该方法效果不明显。对于含有真实环境噪声的带噪语音,该方法能获得比基线系统更好的性能。
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| 关 键 词： | 计算机应用 中文信息处理 大词汇连续语音识别 小波分析 声学模型 |
| 文章编号： | 1003-0077（2006）02-0060-06 |
| 收稿时间： | 2005-01-25 |
| 修稿时间： | 2005-04-15 |
A Study on Robustness of Large Vocabulary Chinese Continuous Speech Recognition System Based on Wavelet Analysis |
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| YAN Long,LIU Gang,GUO Jun.A Study on Robustness of Large Vocabulary Chinese Continuous Speech Recognition System Based on Wavelet Analysis[J].Journal of Chinese Information Processing,2006,20(2):62-67. |
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| Authors: | YAN Long LIU Gang GUO Jun |
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| Affiliation: | School of Information Engineering , Beijing University of Posts and Telecommunications |
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| Abstract: | In this paper wavelet decomposition is used to decompose speech signal into five levels.The wavelet coefficients of each part were reconstructed.Because different frequencies of the speech signal have different influence on the performance of the system,the acoustic model of each level was trained and tested.The experimental results show that the method of this paper is effective on gauss white noise and real environmental noise.However it is not effective on pink noise. |
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| Keywords: | computer application Chinese information processing large vocabulary continuous speech recognition wavelet analysis acoustic model |
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