{"title":"Window optimization in linear prediction analysis","authors":"W. Chu","doi":"10.1109/TSA.2003.818213","DOIUrl":null,"url":null,"abstract":"The autocorrelation method of linear prediction (LP) analysis relies on a window for data extraction. We propose an approach to optimize the window which is based on gradient-descent. It is shown that the optimized window can enhance the performance of LP-based speech coding algorithms; in most instances, improvement in performance comes at no additional computational cost, since it merely requires a window replacement.","PeriodicalId":13155,"journal":{"name":"IEEE Trans. Speech Audio Process.","volume":"24 1","pages":"626-635"},"PeriodicalIF":0.0000,"publicationDate":"2003-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Trans. Speech Audio Process.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TSA.2003.818213","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
The autocorrelation method of linear prediction (LP) analysis relies on a window for data extraction. We propose an approach to optimize the window which is based on gradient-descent. It is shown that the optimized window can enhance the performance of LP-based speech coding algorithms; in most instances, improvement in performance comes at no additional computational cost, since it merely requires a window replacement.
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