Question answering on large news video archive

Author

Chua, Tat-Seng

Author_Institution

Sch. of Comput., Nat. Univ. of Singapore, Singapore

Volume

1

fYear

2003

fDate

18-20 Sept. 2003

Firstpage

289

Abstract

Many users are interested in looking for precise answers when querying the news video archives, while current systems are designed to return only video sequences. This research explores the use of question-answering (QA) to support personalized news video retrieval. Based on the user´s short, imprecise natural language question, with implicit constraints on contents, context, duration and genre of expected videos, the system returns short precise news video fragments as answers. The system uses multi-modal features including visual, audio, speech-to-text, and external on-line news articles to perform the analysis. The system has been tested using 7 days of news video and has been found to be effective.

Keywords

image retrieval; image sequences; information resources; multimedia systems; VideoQA system; audio news article; external on-line news article; multimedia technology; multimodal feature; news video archive; news video question answering system; personalized news video retrieval; querying; speech-to-text news article; video semantic content; video sequence; visual news article; Error correction; Fuses; Multimedia systems; Natural languages; Performance analysis; Speech analysis; Speech recognition; System analysis and design; Video sequences; Watches;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the 3rd International Symposium on

Print_ISBN

953-184-061-X

Type

conf

DOI

10.1109/ISPA.2003.1296910

Filename

1296910