{"title":"基于三个分类器并行融合的说话人分割","authors":"S. Ouamour, H. Sayoud, M. Guerti","doi":"10.1109/ICSCS.2009.5412583","DOIUrl":null,"url":null,"abstract":"In this paper, we deal with the problem of speaker segmentation. This speciality consists in splitting the audio document into homogeneous areas. Each area is attributed to one speaker [1]. Speaker segmentation (or speaker change detection) consists in detecting the points where the speaker identity changes, in a multi-speaker audio stream. These points or times are called “Break Points” [2].","PeriodicalId":126072,"journal":{"name":"2009 3rd International Conference on Signals, Circuits and Systems (SCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Speaker segmentation using parallel fusion between three classifiers\",\"authors\":\"S. Ouamour, H. Sayoud, M. Guerti\",\"doi\":\"10.1109/ICSCS.2009.5412583\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we deal with the problem of speaker segmentation. This speciality consists in splitting the audio document into homogeneous areas. Each area is attributed to one speaker [1]. Speaker segmentation (or speaker change detection) consists in detecting the points where the speaker identity changes, in a multi-speaker audio stream. These points or times are called “Break Points” [2].\",\"PeriodicalId\":126072,\"journal\":{\"name\":\"2009 3rd International Conference on Signals, Circuits and Systems (SCS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 3rd International Conference on Signals, Circuits and Systems (SCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSCS.2009.5412583\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 3rd International Conference on Signals, Circuits and Systems (SCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSCS.2009.5412583","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Speaker segmentation using parallel fusion between three classifiers
In this paper, we deal with the problem of speaker segmentation. This speciality consists in splitting the audio document into homogeneous areas. Each area is attributed to one speaker [1]. Speaker segmentation (or speaker change detection) consists in detecting the points where the speaker identity changes, in a multi-speaker audio stream. These points or times are called “Break Points” [2].