{"title":"通过细化话语检测,增强说话人分割","authors":"Min Yang, Zhaohui Wu, Yingchun Yang","doi":"10.1109/ICME.2005.1521419","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce an elaborate utterance detection algorithm to enhance speaker segmentation. Silence detector, further divider and audio type classifier are employed in this elaborate utterance detection, to make this algorithm adaptive for both silent and noisy environments. Open-set verification testing has taken on the Hub4-NE broadcasts database. The experiment results show that this enhanced segmentation method can provide better information for speaker models.","PeriodicalId":244360,"journal":{"name":"2005 IEEE International Conference on Multimedia and Expo","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Enhance speaker segmentation by elaborating utterance detection\",\"authors\":\"Min Yang, Zhaohui Wu, Yingchun Yang\",\"doi\":\"10.1109/ICME.2005.1521419\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we introduce an elaborate utterance detection algorithm to enhance speaker segmentation. Silence detector, further divider and audio type classifier are employed in this elaborate utterance detection, to make this algorithm adaptive for both silent and noisy environments. Open-set verification testing has taken on the Hub4-NE broadcasts database. The experiment results show that this enhanced segmentation method can provide better information for speaker models.\",\"PeriodicalId\":244360,\"journal\":{\"name\":\"2005 IEEE International Conference on Multimedia and Expo\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-07-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2005 IEEE International Conference on Multimedia and Expo\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICME.2005.1521419\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 IEEE International Conference on Multimedia and Expo","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICME.2005.1521419","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Enhance speaker segmentation by elaborating utterance detection
In this paper, we introduce an elaborate utterance detection algorithm to enhance speaker segmentation. Silence detector, further divider and audio type classifier are employed in this elaborate utterance detection, to make this algorithm adaptive for both silent and noisy environments. Open-set verification testing has taken on the Hub4-NE broadcasts database. The experiment results show that this enhanced segmentation method can provide better information for speaker models.