Speech enhancement using bionic wavelet transform and adaptive threshold function

Yang Xi, Liu Bing-wu, Yan Fang
{"title":"Speech enhancement using bionic wavelet transform and adaptive threshold function","authors":"Yang Xi, Liu Bing-wu, Yan Fang","doi":"10.1109/CINC.2010.5643844","DOIUrl":null,"url":null,"abstract":"By the use of the Bionic Wavelet Transform and adaptive threshold function, this paper presents an improved wavelet-based speech enhancement method, Adaptive Bionic Wavelet Speech Enhancement. Due to the integration of human auditory system model into the wavelet transform, the main advantage of the proposed method is that the over thresholding of speech segments which is usually occurred in conventional wavelet-based speech enhancement schemes can be avoided. Then it can track the variation of noisy speech without the estimation of the a priori knowledge of SNR. As a consequence, the enhanced speech quality of the proposed method can be increased substantially from those of conventional approaches.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second International Conference on Computational Intelligence and Natural Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CINC.2010.5643844","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

By the use of the Bionic Wavelet Transform and adaptive threshold function, this paper presents an improved wavelet-based speech enhancement method, Adaptive Bionic Wavelet Speech Enhancement. Due to the integration of human auditory system model into the wavelet transform, the main advantage of the proposed method is that the over thresholding of speech segments which is usually occurred in conventional wavelet-based speech enhancement schemes can be avoided. Then it can track the variation of noisy speech without the estimation of the a priori knowledge of SNR. As a consequence, the enhanced speech quality of the proposed method can be increased substantially from those of conventional approaches.
基于仿生小波变换和自适应阈值函数的语音增强
利用仿生小波变换和自适应阈值函数,提出了一种改进的基于小波的语音增强方法——自适应仿生小波语音增强。由于将人听觉系统模型集成到小波变换中,该方法的主要优点是避免了传统基于小波的语音增强方案中经常出现的语音段过阈值问题。然后在不估计信噪比先验知识的情况下,对含噪语音的变化进行跟踪。因此,与传统方法相比,该方法的语音质量得到了显著提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信