Endpoint Detection of Isolated Words Using Center of Gravity Method

M. B. Gulmezoglu, R. Edizkan, S. Ergin, A. Barkana
{"title":"Endpoint Detection of Isolated Words Using Center of Gravity Method","authors":"M. B. Gulmezoglu, R. Edizkan, S. Ergin, A. Barkana","doi":"10.1109/SIU.2007.4298665","DOIUrl":null,"url":null,"abstract":"In this study, center of gravity (COG) method is proposed to detect endpoints of isolated words. Common vector approach (CVA) is employed to evaluate the effect of the proposed method in the isolated word recognition. Since the CVA method is sensitive to shifts through the time axis, endpoint detection of words is extremely important. For the comparison purpose, one of the well-known endpoint detection methods is also used together with CVA. The recognition rates obtained by using COG and CVA methods for Tl-digit database are greater than those obtained by using other endpoint detection and CVA methods.","PeriodicalId":315147,"journal":{"name":"2007 IEEE 15th Signal Processing and Communications Applications","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE 15th Signal Processing and Communications Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIU.2007.4298665","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In this study, center of gravity (COG) method is proposed to detect endpoints of isolated words. Common vector approach (CVA) is employed to evaluate the effect of the proposed method in the isolated word recognition. Since the CVA method is sensitive to shifts through the time axis, endpoint detection of words is extremely important. For the comparison purpose, one of the well-known endpoint detection methods is also used together with CVA. The recognition rates obtained by using COG and CVA methods for Tl-digit database are greater than those obtained by using other endpoint detection and CVA methods.
用重心法检测孤立词的端点
在本研究中,提出了重心(COG)方法来检测孤立词的端点。用公共向量法(CVA)对该方法在孤立词识别中的效果进行了评价。由于CVA方法对时间轴的偏移很敏感,因此单词的端点检测非常重要。为了比较,我们还将一种众所周知的端点检测方法与CVA结合使用。采用COG和CVA方法对Tl-digit数据库的识别率高于其他端点检测和CVA方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信