Convolutive Sparse Non-negative Matrix Factorization for Windy Speech

摘要：

This paper presents a method for suppressing wind noise in a single channel recording of speech outdoors. This proposed method is based on the convolutive extension of Sparse Non-negative Matrix Factorization, in which a convolutive model is used to attenuate the acoustic effect of wind noise based on wind noise codebook estimated from a recording of pure wind noises. The extended method is convolutive in time domain, thus the potential interframe information of the speech can be exploited to get a more effective result. In the paper, we first exploit the characteristics of wind noise, then focus on the extension method of SNMF and demonstrate its effectiveness on wind noise reduction.

关键词： wind noise reduction sparse non-negative matrix factorization (SNMF) convolutive sparse non-negative matrix factorization (c-SNMF)

作者: Lai Xiaoqiang Li Shuangtian Yang Jie

作者单位: Institute of Acoustics, Chinese Academy of Sciences, Beijing, 100190, China

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 494-497

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）