{"title":"研究环境对语音分离ICA性能的影响","authors":"V. Sedlák, D. Durackova, R. Záluský","doi":"10.1109/ELEKTRO.2012.6225578","DOIUrl":null,"url":null,"abstract":"Speech signals extraction is becoming more and more important in variety applications such as mobile phones, conference equipments, radars and others. This paper presents a blind method to enhance and separate speech signals in noisy environment. The proposed technique exploits the independent component analysis (ICA) to separate speech signals. We investigate impact of environment (noise, number of sources and their location, etc.) for performance of this method. For evaluation of performance are used parameters source-to-interference ratio SIR, source-to-distortion ration SDR and source-to-artifacts ration SAR.","PeriodicalId":343071,"journal":{"name":"2012 ELEKTRO","volume":"168 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Investigation impact of environment for performance of ICA for speech separation\",\"authors\":\"V. Sedlák, D. Durackova, R. Záluský\",\"doi\":\"10.1109/ELEKTRO.2012.6225578\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Speech signals extraction is becoming more and more important in variety applications such as mobile phones, conference equipments, radars and others. This paper presents a blind method to enhance and separate speech signals in noisy environment. The proposed technique exploits the independent component analysis (ICA) to separate speech signals. We investigate impact of environment (noise, number of sources and their location, etc.) for performance of this method. For evaluation of performance are used parameters source-to-interference ratio SIR, source-to-distortion ration SDR and source-to-artifacts ration SAR.\",\"PeriodicalId\":343071,\"journal\":{\"name\":\"2012 ELEKTRO\",\"volume\":\"168 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 ELEKTRO\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ELEKTRO.2012.6225578\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 ELEKTRO","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ELEKTRO.2012.6225578","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Investigation impact of environment for performance of ICA for speech separation
Speech signals extraction is becoming more and more important in variety applications such as mobile phones, conference equipments, radars and others. This paper presents a blind method to enhance and separate speech signals in noisy environment. The proposed technique exploits the independent component analysis (ICA) to separate speech signals. We investigate impact of environment (noise, number of sources and their location, etc.) for performance of this method. For evaluation of performance are used parameters source-to-interference ratio SIR, source-to-distortion ration SDR and source-to-artifacts ration SAR.