Multimedia summaries of broadcast news

Abstract

Increasing amounts of text, audio, and video content has fueled efforts to provide direct, content based access to these materials. Summaries are often necessary to enable timely relevancy assessments, information extraction, or information analysis from source material. Whereas text summarization research is receiving increasing attention, comparatively few investigators have examined video summarization. We report on the extension of a broadcast news access system to provide multimedia summaries. We briefly overview our system for video analysis, focusing on our novel integration of image, speech and language processing techniques to support automated video summarization. We outline algorithms for proper name and keyphrase extraction, story segmentation, and key frame extraction which together underpin our current ability to automatically summarize video. We describe the systems ability to generate multimedia video summaries tailored to a user query. We discuss evaluation metrics for measuring the (quality) value of these summary artifacts.