一种低信噪比环境下的语音端点检测算法  

A speech endpoint detection method in low SNR environment

作　　者：卜玉婷 曾庆宁[1] 郑展恒[1] BU Yuting;ZENG Qingning;ZHENG Zhanheng(Guilin University of Electronic Technology,Key Laboratory of Cognitive Radio and Information Processing of Ministry of Education,Guilin 541004,Guangxi,China)

机构地区：[1]桂林电子科技大学“认知无线电与信息处理”教育部重点实验室,广西桂林541004

出　　处：《声学技术》2020年第5期592-602,共11页Technical Acoustics

基　　金：广西自然科学基金重点项目(2016GXNSFDA380018);国家自然科学基金项目(61461011);教育部重点实验室主任基金项目(CRKL160107)。

摘　　要：端点检测技术是语音信号处理的关键技术之一,为提高低信噪比环境下端点检测的准确率和稳健性,提出了一种非平稳噪声抑制和调制域谱减结合功率归一化倒谱距离的端点检测算法。该算法首先通过抑制非平稳噪声再采用调制域谱减消除残余噪声来提升信噪比,减少语音失真。然后再提取每帧信号的功率归一化倒谱系数,计算每帧信号与背景噪声的功率归一化倒谱距离。最后将该倒谱距离作为检测参数,采用双门限判决方法进行端点检测。实验结果表明,该端点检测算法对语音帧和噪声帧具有较好的区分性。此外,在低信噪比环境下,所提出的算法对于不同类型的噪声都具有较好的稳健性。Endpoint detection technique is one of the key techniques in speech signal processing.In order to improve the accuracy and robustness of endpoint detection in low signal-to-noise ratio(SNR)environment,an endpoint detection algorithm based on non-stationary noise suppression and modulation domain spectral subtraction combining with power normalized cepstrum distance is proposed.Firstly,the algorithm suppresses non-stationary noise and uses modulation domain spectral subtraction to eliminate residual noise,so as to improve signal-to-noise ratio and reduce speech distortion.Then,the power normalized cepstrum coefficients of each frame signal are extracted.By calculating the power normalized cepstrum distance between each frame signal and background noise,a robust endpoint detection parameter is obtained.Finally,the double threshold method is used to perform endpoint detection by using this parameter.The experimental results show that the speech frames and noise frames can be effectively distinguished by endpoint detection algorithm.Furthermore,the proposed method achieves better anti-noise robustness for different types of noises even in a low SNR environment.

关 键 词：低信噪比 瞬态抑制 调制域 功率归一化倒谱系数 倒谱距离 端点检测 

分 类 号：TN912.35[电子电信—通信与信息系统]