基于LMS减噪与改进的双门限语音端点检测方法

doi:10.16182/j.issn1004731x.joss.201709011

系统仿真学报 ›› 2017, Vol. 29 ›› Issue (9): 1950-1960.doi: 10.16182/j.issn1004731x.joss.201709011

基于LMS减噪与改进的双门限语音端点检测方法

朱春利¹, 李昕^1,2,3

1.上海大学机电工程与自动化学院,上海 200072;
2.南京大学电子科学与工程系,南京 210093;
3.中科院自动化所模式识别国家重点实验室,北京100080

收稿日期:2017-05-20 发布日期:2020-06-02
作者简介:朱春利(1994-),男,安徽,硕士生,研究方向为语音信号处理、语音的端点检测;李昕(1970-),男,江苏盐城,博士,副研究员,研究方向为语音识别、智能机器人。
基金资助:
上海市科委重点项目(14DZ1206302)

Speech Endpoint Detection Method Based on LMS Noise Reduction and Improved Dual-threshold

Zhu Chunli¹, Li Xin^1,2,3

1. School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200072, China;
2. Department of Electronic and Information Engineering, Nanjing University, Nanjing 210093, China;
3. State Key Lab of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China

Received:2017-05-20 Published:2020-06-02

摘要/Abstract

摘要： 低信噪比环境下语音的端点检测在语音处理中占有十分重要的地位。对于一个受到加性噪声污染的语音信号通常采用滤波的方式,能够抑制噪声,并使原始语音保持相对不变。提出了一种基于最小均方误差(LMS)自适应滤波减噪与改进的双门限语音端点检测算法,在进行双参数双门限法端点检测的前后进行双重中值滤波平滑处理。通过Matlab仿真,将提出的语音端点检测方法与其它的方法进行对比,在信噪比较低的噪声环境下使得语音的端点检测效果具有更优的准确率与稳健性。

关键词: 端点检测, LMS自适应滤波, 减噪, 双门限法, 中值滤波, 平滑处理

Abstract: Endpoint detection of speech in low signal-to-noise ratio plays a very important role in voice processing. For a speech signal that is polluted by additive noise, it is possible to suppress the noise and keep the original speech relatively constant. A dual-threshold speech endpoint detection algorithm was proposed based on the least mean squares error (LMS) adaptive filtering. Dual median filtering smoothing was performed before and after double-parameter double-threshold detection. Through the Matlab simulation, the speech endpoint detection method was compared with other methods. In the noise environment with low signal-to-noise ratio, the endpoint detection effect of speech has better accuracy and robustness.

Key words: endpoint detection, LMS adaptive filtering, noise reduction, double threshold method, median filter, smoothing

中图分类号:

TN912.3

朱春利, 李昕. 基于LMS减噪与改进的双门限语音端点检测方法[J]. 系统仿真学报, 2017, 29(9): 1950-1960.

Zhu Chunli, Li Xin. Speech Endpoint Detection Method Based on LMS Noise Reduction and Improved Dual-threshold[J]. Journal of System Simulation, 2017, 29(9): 1950-1960.

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基于LMS减噪与改进的双门限语音端点检测方法

Speech Endpoint Detection Method Based on LMS Noise Reduction and Improved Dual-threshold

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