{"title":"混响声环境中唯一声源活动周期的盲检测","authors":"R. M. Nickel","doi":"10.1109/SAM.2008.4606894","DOIUrl":null,"url":null,"abstract":"Blind separation and dereverberation of acoustic sources is still considered a very challenging task despite many years of research and the availability of increasingly powerful computation engines. The complexity of the task can be significantly reduced for sources that exhibit sufficiently long exclusive activity periods (EAPs). EAPs are time intervals during which only one source is active and all other sources are inactive (i.e. zero). During EAPs the estimation of the underlying system parameters simplifies from a MIMO type to a SIMO type. The existence of EAPs is not guaranteed for arbitrary signal classes. EAPs occur very frequently, however, in recordings of conversational speech. In this paper we propose a new low complexity method for EAP detection which significantly outperforms earlier approaches.","PeriodicalId":422747,"journal":{"name":"2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop","volume":"24 4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Blind detection of exclusive source activity periods in reverberant acoustic environments\",\"authors\":\"R. M. Nickel\",\"doi\":\"10.1109/SAM.2008.4606894\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Blind separation and dereverberation of acoustic sources is still considered a very challenging task despite many years of research and the availability of increasingly powerful computation engines. The complexity of the task can be significantly reduced for sources that exhibit sufficiently long exclusive activity periods (EAPs). EAPs are time intervals during which only one source is active and all other sources are inactive (i.e. zero). During EAPs the estimation of the underlying system parameters simplifies from a MIMO type to a SIMO type. The existence of EAPs is not guaranteed for arbitrary signal classes. EAPs occur very frequently, however, in recordings of conversational speech. In this paper we propose a new low complexity method for EAP detection which significantly outperforms earlier approaches.\",\"PeriodicalId\":422747,\"journal\":{\"name\":\"2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop\",\"volume\":\"24 4\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAM.2008.4606894\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAM.2008.4606894","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Blind detection of exclusive source activity periods in reverberant acoustic environments
Blind separation and dereverberation of acoustic sources is still considered a very challenging task despite many years of research and the availability of increasingly powerful computation engines. The complexity of the task can be significantly reduced for sources that exhibit sufficiently long exclusive activity periods (EAPs). EAPs are time intervals during which only one source is active and all other sources are inactive (i.e. zero). During EAPs the estimation of the underlying system parameters simplifies from a MIMO type to a SIMO type. The existence of EAPs is not guaranteed for arbitrary signal classes. EAPs occur very frequently, however, in recordings of conversational speech. In this paper we propose a new low complexity method for EAP detection which significantly outperforms earlier approaches.