{"title":"Wavelet transform-based speech enhancement","authors":"E. Ambikairajah, G. Tattersall, A. Davis","doi":"10.21437/ICSLP.1998-348","DOIUrl":null,"url":null,"abstract":"This paper describes a speech enhancement system using a novel combination of a Fast Wavelet Transform structure, together with “Wiener filtering” in the wavelet domain. The specific application of interest is the enhancement of speech when a cellular phone is used within a moving vehicle. Subjective tests carried out using speech with additive vehicle noise at a signal-to-noise ratio of 10 dB indicate that the Wavelet transform-based Wiener filtering approach works well. In particular, the technique was compared to several other common enhancement methods such as thresholding applied in the wavelet domain, FFT-based Wiener filtering, and spectral subtraction, and was found to outperform these other techniques.","PeriodicalId":117113,"journal":{"name":"5th International Conference on Spoken Language Processing (ICSLP 1998)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"31","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"5th International Conference on Spoken Language Processing (ICSLP 1998)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21437/ICSLP.1998-348","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 31
Abstract
This paper describes a speech enhancement system using a novel combination of a Fast Wavelet Transform structure, together with “Wiener filtering” in the wavelet domain. The specific application of interest is the enhancement of speech when a cellular phone is used within a moving vehicle. Subjective tests carried out using speech with additive vehicle noise at a signal-to-noise ratio of 10 dB indicate that the Wavelet transform-based Wiener filtering approach works well. In particular, the technique was compared to several other common enhancement methods such as thresholding applied in the wavelet domain, FFT-based Wiener filtering, and spectral subtraction, and was found to outperform these other techniques.