{"title":"Speech Enhancement For Hearing Aids Using A Microphone Array","authors":"A. Ganeshkumar, J. Hammond, C. G. Rice","doi":"10.1109/ASPAA.1991.634122","DOIUrl":null,"url":null,"abstract":"Our approach is based on enhancing the Short Time Spectral Amplitude (STSA) of degraded speech using the spectral subtraction algorithm. The use of spectral subtraction to enhance speech has been studied quite extensively in the past [1,2]. These studies have generally shown an increase in speech quality but the gain in intelligibility has been insignificant. The lack of improvement in intelligibility can be atmbiited to two main factors. The first being that since all previous work on the application of spectral subtraction algorithm have been confined to single input systems, the noise short time spectrum can only be estimated during non-speech activity periods. This approach not only requires accurate speechhion-speech activity detection a difficult task, particularly at low signal to noise ratiosbut also requires the noise to be sufficiently stationary for the estimate to be used during the subsequent speech period. The second factor for the lack of improvement in intelligibility is due to the annoying 'musical' type of residual noise introduced by spectral subtraction processing. This residual noise may distract the listener from the speech.","PeriodicalId":146017,"journal":{"name":"Final Program and Paper Summaries 1991 IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics","volume":"521 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Final Program and Paper Summaries 1991 IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASPAA.1991.634122","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Our approach is based on enhancing the Short Time Spectral Amplitude (STSA) of degraded speech using the spectral subtraction algorithm. The use of spectral subtraction to enhance speech has been studied quite extensively in the past [1,2]. These studies have generally shown an increase in speech quality but the gain in intelligibility has been insignificant. The lack of improvement in intelligibility can be atmbiited to two main factors. The first being that since all previous work on the application of spectral subtraction algorithm have been confined to single input systems, the noise short time spectrum can only be estimated during non-speech activity periods. This approach not only requires accurate speechhion-speech activity detection a difficult task, particularly at low signal to noise ratiosbut also requires the noise to be sufficiently stationary for the estimate to be used during the subsequent speech period. The second factor for the lack of improvement in intelligibility is due to the annoying 'musical' type of residual noise introduced by spectral subtraction processing. This residual noise may distract the listener from the speech.