通过细化话语检测,增强说话人分割

Min Yang, Zhaohui Wu, Yingchun Yang
{"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}
引用次数: 1

摘要

在本文中,我们介绍了一种精细的话语检测算法来增强说话人分割。该算法在语音检测中采用了沉默检测器、进一步分频器和音频类型分类器,使该算法能够适应噪声环境和沉默环境。对Hub4-NE广播数据库进行了开集验证测试。实验结果表明,这种增强的分割方法可以为说话人模型提供更好的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Lossless image compression with tree coding of magnitude levels Maximizing the profit for cache replacement in a transcoding proxy Pre-Attentional Filtering in Compressed Video Annotation and detection of blended emotions in real human-human dialogs recorded in a call center Fast inter frame encoding based on modes pre-decision in H.264
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1