作者其他论文
文献详情
UNSUPERVISED BROADCAST NEWS STORY SEGMENTATION USING DISTANCE DEPENDENT CHINESE RESTAURANT PROCESSES
文献类型:会议
作者:Yang, Chao[1]  Xie, Lei[2]  Zhou, Xiangzeng[3]  
机构:[1]Shaanxi Provincial Key Laboratory of Speech and Image Information Processing, School of Computer Science, Northwestern Polytechnical University, Xi'an, China
[2]Shaanxi Provincial Key Laboratory of Speech and Image Information Processing, School of Computer Science, Northwestern Polytechnical University, Xi'an, China
[3]Shaanxi Provincial Key Laboratory of Speech and Image Information Processing, School of Computer Science, Northwestern Polytechnical University, Xi'an, China
年:2014
通讯作者:Yang, C (reprint author), Northwestern Polytech Univ, Sch Comp Sci, Shaanxi Prov Key Lab Speech & Image Informat Proc, Xian 710072, Peoples R China.
会议名称:2014 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
页码范围:4062-4066
会议开始日期:2014-05-04
收录情况:EI(20143218037996)  CPCI-S(WOS:000343655304017)  
所属部门:计算机学院
人气指数:1338
浏览次数:1322
语言:外文
摘要:
Traditional unsupervised broadcast news story segmentation approaches have to set the segmentation number manually, while this number is often unknown in real-world applications. In this paper, we solve this problem by modeling the generative process of stories as distance dependent Chinese restaurant process (dd-CRP) mixtures. We cut a news program into fixed-size text blocks and consider these blocks in the same story are generated from a story-specific topic. Specifically, we add a dd-CRP pri ...More
0
评论(0 条评论)
登录