SPORTS AUDIO SEGMENTATION AND CLASSIFICATION

摘要：

The audio stream is an important component of a sports video. In this paper, we present a system for audio segmentation and classification, which can segment and classify the sports audio stream into speech, non-speech very well. The novel point in our research is that we apply the segmentation and clustering method which is often used in speaker diarization system for broadcast news to the analysis of sports videos. After the segmentation and Bayesian Information Criterion (BIC) clustering is performed, Gaussian Mixture Model (GMM) is used in the classifier to identify the kind of sound for each segment. Experiments on a database composed of 6 hour audio stream in the Eurosport TV program show that the average accuracy can reach 87.3% on segmentation and classification. This research is very useful for analyzing the content of sports videos in detail.

关键词： audio segmentation and classification sports audio GMM content analysis

作者: Jun Huang Yuan Dong Jiqing Liu Chengyu Dong Haila Wang

作者单位: Beijing University of Posts and Telecommunications, Beijing France Telecom Research & Development Center, Beijing

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Network Infrastructure and Digital Content(2009年IEEE网络基础设施与数字内容国际会议 IEEE IC-NIDC2009)

会议地点: 北京

会议语种:英文

页码: 379-383

在线出版日期: 2009-11-06（万方平台首次上网日期，不代表论文的发表时间）