Compilation of dictionaries for semantic attribute analysis of television news captions

With the increase in the amount of video that is broadcast daily, there is an increasing need for storage of video in a systematic way for future reuse and retrieval. In particular, from the viewpoint of importance and usability, it is desirable to index news videos. For adequate automatic indexing based on the text information in the video, it is not sufficient to apply the simple index extraction and annotation methods which have been widely used in conventional methods. It is important to select index candidates with reference to semantic attributes. The purpose of this study is to compile dictionaries which are needed for analyzing the semantic attributes of captions (noun phrases) in TV news videos. We describe the process by which words are extracted from text corpora and a thesaurus for storage on the basis of specified conditions. The quality of the dictionaries is examined by analysis of the semantic attributes of the words appearing in actual news videos, and the results are presented. In evaluation experiments in which an existing proper noun dictionary and temporal noun dictionary were combined and used, a recall of 79 to 93% and a precision of 41 to 71% were obtained. Although the precision is low in this result, it is concluded that the compiled dictionaries are of practical use for indexing since the recall is more important in that case. © 2003 Wiley Periodicals, Inc. Syst Comp Jpn, 34(12): 32–44, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10417