摘要
传统的小波去噪算法是一种有效的去除白噪声的算法,为了能够去除多种有包噪声,本文提出了基于双正交小波包分解的自适应阈值语音增强方法,该方法能够自适应地跟踪噪声的水平,以此来更新所选阈值,同时采用动态阈值方法去除噪声,从而能有效地去除或降低多种有色噪声,实验结果表明,该方法由于能够在处理过程中保证相位不失真,从而性能优于基于正交小波分解的去噪方法。
Traditional threshold de-noising algorithm in wavelet domain is effective only for reducing white noise. In order to eliminate many kinds of noises, a speech enhancement approach with adaptive threshold based on bi-orthogonal wavelet packet decomposition is proposed in this paper. This method updates the threshold by adaptively tracking the level of the noise and a dynamic threshold is used for reducing noise. Experimental results show that the pro- posed approach outperforms orthogonal wavelet based de-noising approaches for speech enhancement and can efficiently suppress three kinds of noises.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2008年第10期2135-2140,共6页
Chinese Journal of Scientific Instrument
基金
北京市教委科技发展计划项目(KM200710005001)
北京市自然科学基金(4042009)资助项目
关键词
语音增强
小波变换
自适应阈值
speech enhancement
wavelet transform
adaptive threshold
