| 基于调制域谱减法的鲁棒性说话人识别 |
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| 引用本文： | 程小伟,王健,曾庆宁,谢先明,龙超.基于调制域谱减法的鲁棒性说话人识别[J].科学技术与工程,2017,17(3). |
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| 作者姓名： | 程小伟 王健 曾庆宁 谢先明 龙超 |
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| 作者单位： | 桂林电子科技大学 信息与通信学院,桂林电子科技大学 信息与通信学院,桂林电子科技大学 信息与通信学院,桂林电子科技大学 信息与通信学院,桂林电子科技大学 信息与通信学院 |
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| 基金项目： | 国家自然科学基金(No.61461011);广西自然科学基金(No.2014GXNSFBA118273)。 |
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| 摘 要： | 针对说话人识别性能在噪声环境下急剧下降的问题,提出了基于调制域谱减法的鲁棒性说话人识别方法。首先在说话人识别前端通过调制域谱减法对含噪语音进行增强处理,然后通过Gammatone滤波器组提取对噪声具有抑制作用的特征,最后与说话人模型进行匹配识别。仿真结果表明,运用此方法能显著抑制噪声对说话人识别系统的影响,提高系统的识别率。
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| 关 键 词： | 调制域 谱减 说话人识别 Gammatone滤波器组 鲁棒性 |
| 收稿时间： | 2016/7/8 0:00:00 |
| 修稿时间： | 2016/9/10 0:00:00 |
Robust speaker recognition based on modulation domain spectral subtraction |
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| Cheng Xiaowei,Wang Jian,Zeng Qingning,Xie Xianming and Long Chao.Robust speaker recognition based on modulation domain spectral subtraction[J].Science Technology and Engineering,2017,17(3). |
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| Authors: | Cheng Xiaowei Wang Jian Zeng Qingning Xie Xianming and Long Chao |
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| Institution: | School of Information and Communication,Guilin University Of Electronic Technology,Guilin,School of Information and Communication,Guilin University Of Electronic Technology,Guilin,School of Information and Communication,Guilin University Of Electronic Technology,Guilin,School of Information and Communication,Guilin University Of Electronic Technology,Guilin |
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| Abstract: | In order to solve the problem that recognition rate decreases significantly under noisy environment, a robust speaker recognition method based on Modulation Domain Spectral Subtraction is proposed. The method uses spectral subtraction in modulation domain to improve the intelligibility at the front-end, then extraction the robust speaker feature through Gammatone filter bank, and finally the feature will be matched with the model of the speaker. The simulation results show that the proposed method can significantly suppress the effect of noise on the speaker recognition system and thus improve the recognition rate of the system. |
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| Keywords: | modulation domain spectral subtraction speaker recognition Gammatone filter bank robustness |
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