一种分层阈值优化的语音感知小波去噪方法.pdfVIP

第26 卷第2 期 湖南文理学院学报( 自然科学版) Vol . 26 No. 2 2014 年6 月 Journal of Hunan University of Arts and Science(Natural Science Edition) Jun. 2014 doi: 10.3969/j.issn.1672-6146.2014.02.008 一种分层阈值优化的语音感知小波去噪方法 ∗ 曹斌芳 , 彭光含, 彭元杰, 黎小琴 (湖南文理学院 物理与电子科学学院, 湖南 常德, 415000) 摘 要: 通过分析含噪语音信号的特点, 引入能够兼顾人耳听觉特性的听觉感知小波变换, 构造了新的小波 阈值函数, 并对小波变换分解后的阈值进行基于微粒群算法的分层优化. 仿真实验表明, 该方法在不同信噪 比条件下均具有较好的去噪性能, 语音的可懂度和听觉效果得到有效提高. 关键词: 语音去噪; 听觉感知小波变换; 分层阈值; 微粒群算法 中图分类号: TN 912 文章编号: 1672-6146(2014)02-0035-05 Speech de-noising algorithm of perception wavelet transform based on hierarchical threshold optimization CAO BinFang, PENG GuangHan, PENG YuanJie, LI XiaoQin (College of Physics and Electronics Science, Hunan University of Arts and Science, Changde 415000, China) Abstract: By analyzing the characteristic of noisy speech signals, audio perception wavelet transform was introduced, which considered human auditory effect. New wavelet threshold function was constructed and hierarchical optimization was performed based on particle swarm optimization algorithm after wavelet transform. Simulation indicated that the proposed method had a good de-noising effect under circumstances of different signal-noise-ratio(SNR) , improved speech intelligibility and auditory effect. Key words: speech de-noising; auditory perception wavelet transform; Hierarchical threshold; particle swarm optimization 在语音通信过程中, 常常会受到环境噪声的影响, 这些噪声的存在严重影响了语音的质量, 导致接 收者收到的语音信号并非纯净的原始信号. 语音信号的噪声消除技术是语音信号处理的一个重要分支, 主要是完成在保证语音可懂度