{"title":"PIRS:基于伪反转的语音信号恢复","authors":"H. Ajorloo, A. Lakdashti, M. Manzuri-Shalmani","doi":"10.1109/ISSPIT.2007.4458131","DOIUrl":null,"url":null,"abstract":"Communication of speech over error prone channels such as wireless channels and internet usually suffers from loss of large number of adjacent samples. In this paper, we propose to make artificial correlation between speech samples which distorts it. By choosing appropriate parameters, one can control this distortion to lie below acceptable ranges. Using this correlation, the receiver can recover lost samples up to a certain limit using our proposed algorithm. Experimental results show that our solution overcomes a previous one reported in the literature specially when the amount of lost samples are below the mentioned limit.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"47 29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"PIRS: Pseudo Inversion Based Recovery of Speech Signals\",\"authors\":\"H. Ajorloo, A. Lakdashti, M. Manzuri-Shalmani\",\"doi\":\"10.1109/ISSPIT.2007.4458131\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Communication of speech over error prone channels such as wireless channels and internet usually suffers from loss of large number of adjacent samples. In this paper, we propose to make artificial correlation between speech samples which distorts it. By choosing appropriate parameters, one can control this distortion to lie below acceptable ranges. Using this correlation, the receiver can recover lost samples up to a certain limit using our proposed algorithm. Experimental results show that our solution overcomes a previous one reported in the literature specially when the amount of lost samples are below the mentioned limit.\",\"PeriodicalId\":299267,\"journal\":{\"name\":\"2007 IEEE International Symposium on Signal Processing and Information Technology\",\"volume\":\"47 29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE International Symposium on Signal Processing and Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSPIT.2007.4458131\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE International Symposium on Signal Processing and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPIT.2007.4458131","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PIRS: Pseudo Inversion Based Recovery of Speech Signals
Communication of speech over error prone channels such as wireless channels and internet usually suffers from loss of large number of adjacent samples. In this paper, we propose to make artificial correlation between speech samples which distorts it. By choosing appropriate parameters, one can control this distortion to lie below acceptable ranges. Using this correlation, the receiver can recover lost samples up to a certain limit using our proposed algorithm. Experimental results show that our solution overcomes a previous one reported in the literature specially when the amount of lost samples are below the mentioned limit.