收稿日期: 2018-01-11
网络出版日期: 2020-03-22
基金资助
国家自然科学基金资助项目(61271213);国家自然科学基金资助项目(61673253);上海市科委重点支撑项目(16010500100);澳门大学科技局资助项目(MYRG 2014-00009-FST);澳门大学科技局资助项目(2016-00053-FST)
Research on compression and denoising of speech signal based on the Takenaka-Malmquist system
Received date: 2018-01-11
Online published: 2020-03-22
语音信号的稀疏表示是语音压缩与降噪等语音处理的关键技术之一. 在匹配追踪(matching pursuit, MP)、正交匹配追踪(orthogonal matching pursuit, OMP)等算法的基础上, 提出了一种基于Takenaka-Malmquist系的贪婪权值算法(a greedy weight algorithm based on the Takenaka-Malmquist system, TMGW). 采用TMGW对语音信号进行重构时只需要较少的分解项数, 从而达到语音压缩的目的. 同时, 根据稀疏分解后信号与噪声在时频面上能量分布不同的特点, 该算法可实现对含噪语音的降噪. 实验结果表明, TMGW比基于自适应Gabor子字典的匹配追踪算法(matching pursuit algorithm based on the adaptive Gabor sub-dictionary, GMP)更适用于语音信号的稀疏表示.
关键词： 基于Takenaka-Malmquist系的贪婪权值算法; 稀疏表示; 语音压缩; 语音降噪
雷娅, 方勇, 张立明 . 基于Takenaka-Malmquist系的语音信号压缩与降噪方法[J]. 上海大学学报(自然科学版), 2020 , 26(1) : 33 -46 . DOI: 10.12066/j.issn.1007-2861.1996
The sparse representation of speech signal is one of the important research directions in speech compression, denoising and other speech processing. On the basis of matching pursuit (MP), orthogonal matching pursuit (OMP) and other greedy algorithms, this paper proposes a greedy weight algorithm based on Takenaka-Malmquist system (TMGW) for the compression of speech signal. This algorithm has the advantage of requiring only fewer decomposition numbers when reconstructing the speech signal, and it does well for achieving the goal of speech compression. Besides, in view of the fact that energy distribution between the signal and noise at time-frequency surface after sparse decomposition is different, this algorithm can realize the purpose of denoising. The experiment results show that the TMGW algorithm is more effective for the sparse representation of speech signal than the matching pursuit algorithm based on the adaptive Gabor sub-dictionary (GMP).
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