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Application of the Keyword Recognition in the Network Monitoring
  • ISSN号:1000-7180
  • 期刊名称:《微电子学与计算机》
  • 时间:0
  • 分类:TP393[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术] TN912.34[电子电信—通信与信息系统;电子电信—信息与通信工程]
  • 作者机构:[1]CollegeofInformationandCommunication,GuilinUniversityofElectronicandTechnology,Guiln541004,6hina
  • 相关基金:This work was supported by the NNatural Science Foundation of Guangxi Province(No.60961002)
中文摘要:

In this paper,the specific application of key words spotting used in the network monitoring is studied,and the keywords spotting is emphasized.The whole monitoring system is divided into two modules:network monitoring and keywords spotting.In the part of network monitoring,this paper adopts a method which is based on ARP spoofing technology to monitor the users’ data,and to obtain the original audio streams.In the part of keywords spotting,the extraction methods of PLP(one of the main characteristic parameters)is studied,and improved feature parameters-PMCC are put forward.Meanwhile,in order to accurately detect syllable,the paper compares the double-threshold method with variance of frequency band method,and use the latter to carry out endpoint detection.Finally,keywords recognition module is built by HMM,and identification results are contrasted under Matlab environment.From the experiment results,a better solution for the application of key words recognition technology in network monitoring is found.

英文摘要:

In this paper, the specific application of key words Spotting used in the network monitoring is studied, and the keywords spotting is emphasized. The whole monitoring system is divided into two mod-ules: network monitoring and keywords spotting. In the part of network monitoring, this paper adopts a method which is based on ARP spoofing technology to monitor the users' data, and to obtain the original audio streams. In the part of keywords spotting, the extraction methods of PLP (one of the main characteristic arameters) is studied, and improved feature parameters- PMCC are put forward. Meanwhile, in order to accurately detect syllable, the paper the double-threshold method with variance of frequency band method, and use the latter to carry out endpoint detection. Finally, keywords recognition module is built by HMM, and identification results are contrasted under Matlab environment. From the experiment results, a better solution for the application of key words recognition technology in network monitoring is found.

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期刊信息
  • 《微电子学与计算机》
  • 中国科技核心期刊
  • 主管单位:中国航天科技集团公司
  • 主办单位:中国航天科技集团公司第九研究院第七七一研究所
  • 主编:李新龙
  • 地址:西安市雁塔区太白南路198号
  • 邮编:710065
  • 邮箱:mc771@163.com
  • 电话:029-82262687
  • 国际标准刊号:ISSN:1000-7180
  • 国内统一刊号:ISSN:61-1123/TN
  • 邮发代号:52-16
  • 获奖情况:
  • 航天优秀期刊,陕西省优秀期刊一等奖
  • 国内外数据库收录:
  • 荷兰文摘与引文数据库,日本日本科学技术振兴机构数据库,中国中国科技核心期刊,中国北大核心期刊(2004版),中国北大核心期刊(2008版),中国北大核心期刊(2011版),中国北大核心期刊(2014版),中国北大核心期刊(2000版)
  • 被引量:17909