A SEGMENTATION METHOD OF NEWS VIDEO STORIES BASED ON ANNOUNCERS VOICEPRINT

摘要：

As an important step of content based news video retrieving and intelligence mining, semantic unit segmentation has attracted many researchers interests. This paper focuses on a new method of news video stories segmentation which is based on the announcers voiccprints. Firstly, the voiccprints included acoustic perception characteristics of all announcers have been extracted, and its Gaussian mixture model will be trained, then the audio clips included announcers and not announcers will be detected by the KL divergence method, at last the semantic units will be segmented under the guidance of video topic caption frames events and special structure knowledge of news program. Finally the 92.58％ recall and the 96.02％ precision have been achieved during more than 2 hours experiment.

关键词： Voiceprint Story unit segmentation Gaussian mizture model News video

作者: XIN-WEN XU GUO-HUI LI JIAN YUAN

作者单位: Information Integration & Training Simulation Lab, Department of System Engineering, School of Information system and Management, National University of Defense Technology, Changsha, Hunan, 410073, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 2749-2753

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）