基于指数模型的含噪语音增强 感知小波包中的阈值及自定义阈值函数 域

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摘要翻译：
针对带噪语音的增强问题，提出了一种基于Teager energy(TE)操作的感知小波包(PWP)系数指数分布建模的阈值确定方法。设计了一个自定义的门限函数，该门限函数基于MU-律和半软阈值函数的结合，将统计导出的门限应用于PWP系数。利用NOIZEUS数据库进行了大量的仿真，验证了该方法对car和多说话人babble噪声破坏语音信号的有效性。在标准的客观测量和包括正式听力测试在内的主观评价方面，该方法在高信噪比和低信噪比下都优于一些现有的语音增强方法。
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英文标题：
《Enhancement of Noisy Speech Exploiting an Exponential Model Based
  Threshold and a Custom Thresholding Function in Perceptual Wavelet Packet
  Domain》
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作者：
Md Tauhidul Islam, Celia Shahnaz, Wei-Ping Zhu, M. Omair Ahmad
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最新提交年份：
2018
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分类信息：

一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Audio and Speech Processing        音频和语音处理
分类描述：Theory and methods for processing signals representing audio, speech, and language, and their applications. This includes analysis, synthesis, enhancement, transformation, classification and interpretation of such signals as well as the design, development, and evaluation of associated signal processing systems. Machine learning and pattern analysis applied to any of the above areas is also welcome.  Specific topics of interest include: auditory modeling and hearing aids; acoustic beamforming and source localization; classification of acoustic scenes; speaker separation; active noise control and echo cancellation; enhancement; de-reverberation; bioacoustics; music signals analysis, synthesis and modification; music information retrieval;  audio for multimedia and joint audio-video processing; spoken and written language modeling, segmentation, tagging, parsing, understanding, and translation; text mining; speech production, perception, and psychoacoustics; speech analysis, synthesis, and perceptual modeling and coding; robust speech recognition; speaker recognition and characterization; deep learning, online learning, and graphical models applied to speech, audio, and language signals; and implementation aspects ranging from system architecture to fast algorithms.
处理代表音频、语音和语言的信号的理论和方法及其应用。这包括分析、合成、增强、转换、分类和解释这些信号，以及相关信号处理系统的设计、开发和评估。机器学习和模式分析应用于上述任何领域也是受欢迎的。感兴趣的具体主题包括：听觉建模和助听器；声波束形成与声源定位；声场景分类；说话人分离；有源噪声控制和回声消除；增强；去混响；生物声学；音乐信号的分析、合成与修饰；音乐信息检索；多媒体音频和联合音视频处理；口语和书面语建模、切分、标注、句法分析、理解和翻译；文本挖掘；言语产生、感知和心理声学；语音分析、合成、感知建模和编码；鲁棒语音识别；说话人识别与特征描述；应用于语音、音频和语言信号的深度学习、在线学习和图形模型；以及从系统架构到快速算法的实现方面。
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英文摘要：
  For enhancement of noisy speech, a method of threshold determination based on modeling of Teager energy (TE) operated perceptual wavelet packet (PWP) coefficients of the noisy speech by exponential distribution is presented. A custom thresholding function based on the combination of mu-law and semisoft thresholding functions is designed and exploited to apply the statistically derived threshold upon the PWP coefficients. The effectiveness of the proposed method is evaluated for car and multi-talker babble noise corrupted speech signals through performing extensive simulations using the NOIZEUS database. The proposed method outperforms some of the state-of-the-art speech enhancement methods both at high and low levels of SNRs in terms of the standard objective measures and the subjective evaluations including formal listening tests.
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PDF链接：
https://arxiv.org/pdf/1802.05962

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关键词：自定义 coefficients localization distribution Architecture 方法 thresholding based 语音 评价