Speech Denoising in White Noise Based on Signal Subspace Low-rank Plus Sparse Decomposition

摘要：

　　In this paper,a new subspace speech enhancement method using low-rank and sparse decomposition is presented.In the proposed method,we firstly structure the corrupted data as a Toeplitz matrix and estimate its effective rank for the underlying human speech signal.Then the low-rank and sparse decomposition is performed with the guidance of speech rank value to remove the noise.Extensive experiments have been carried out in white Gaussian noise condition,and experimental results show the proposed method performs better than conventional speech enhancement methods,in terms of yielding less residual noise and lower speech distortion.

关键词： speech enhancement subspace method low-rank plus sparse decomposition

作者: Shuai yuan Cheng-liSun

作者单位: Science and Technology on Avionics Integration Laboratory,Shanghai,China Nanchang Hangkong University,Nanchang,330063 China

会议类型: 国际会议

会议名称: 2017 International Conference on Electronic Information Technology and Computer Engineering (EITCE 2017)(2017电子信息技术与计算机工程国际会议)(EITCE2017)

会议地点: 珠海

会议语种:英文

页码: 1-4

在线出版日期: 2017-09-23（万方平台首次上网日期，不代表论文的发表时间）