Web-Assisted Annotation, Semantic Indexing and Search of Television and Radio News
M. Dowman, V. Tablan, H. Cunningham, and B. Popov. Proceedings of the 14th International World Wide Web Conference, Chiba, Japan, (2005)http://gate.ac.uk/sale/www05/web-assisted-annotation.pdf.
Abstract
The Rich News system, that can automatically annotate radio and
television news with the aid of resources retrieved from the World
Wide Web, is described. Automatic speech recognition gives a
temporally precise but conceptually inaccurate annotation model.
Information extraction from related web news sites gives the
opposite: conceptual accuracy but no temporal data. Our approach
combines the two for temporally accurate conceptual semantic
annotation of broadcast news. First low quality transcripts of the
broadcasts are produced using speech recognition, and these are
then automatically divided into sections corresponding to
individual news stories. A key phrases extraction component finds
key phrases for each story and uses these to search for web pages
reporting the same event. The text and meta-data of the web pages
is then used to create index documents for the stories in the
original broadcasts, which are semantically annotated using the
KIM knowledge management platform. A web interface then
allows conceptual search and browsing of news stories, and
playing of the parts of the media files corresponding to each news
story. The use of material from the World Wide Web allows much
higher quality textual descriptions and semantic annotations to be
produced than would have been possible using the ASR transcript
directly. The semantic annotations can form a part of the Semantic
Web, and an evaluation shows that the system operates with high
precision, and with a moderate level of recall.
%0 Conference Paper
%1 DowmanEtAl05a
%A Dowman, M.
%A Tablan, V.
%A Cunningham, H.
%A Popov, B.
%B Proceedings of the 14th International World Wide Web Conference
%C Chiba, Japan
%D 2005
%K annotation multimedia news news-video-event-paper phd retrieval thesis-semantic-multimedia video web
%T Web-Assisted Annotation, Semantic Indexing and Search of Television and Radio News
%X The Rich News system, that can automatically annotate radio and
television news with the aid of resources retrieved from the World
Wide Web, is described. Automatic speech recognition gives a
temporally precise but conceptually inaccurate annotation model.
Information extraction from related web news sites gives the
opposite: conceptual accuracy but no temporal data. Our approach
combines the two for temporally accurate conceptual semantic
annotation of broadcast news. First low quality transcripts of the
broadcasts are produced using speech recognition, and these are
then automatically divided into sections corresponding to
individual news stories. A key phrases extraction component finds
key phrases for each story and uses these to search for web pages
reporting the same event. The text and meta-data of the web pages
is then used to create index documents for the stories in the
original broadcasts, which are semantically annotated using the
KIM knowledge management platform. A web interface then
allows conceptual search and browsing of news stories, and
playing of the parts of the media files corresponding to each news
story. The use of material from the World Wide Web allows much
higher quality textual descriptions and semantic annotations to be
produced than would have been possible using the ASR transcript
directly. The semantic annotations can form a part of the Semantic
Web, and an evaluation shows that the system operates with high
precision, and with a moderate level of recall.
@inproceedings{DowmanEtAl05a,
abstract = {The Rich News system, that can automatically annotate radio and
television news with the aid of resources retrieved from the World
Wide Web, is described. Automatic speech recognition gives a
temporally precise but conceptually inaccurate annotation model.
Information extraction from related web news sites gives the
opposite: conceptual accuracy but no temporal data. Our approach
combines the two for temporally accurate conceptual semantic
annotation of broadcast news. First low quality transcripts of the
broadcasts are produced using speech recognition, and these are
then automatically divided into sections corresponding to
individual news stories. A key phrases extraction component finds
key phrases for each story and uses these to search for web pages
reporting the same event. The text and meta-data of the web pages
is then used to create index documents for the stories in the
original broadcasts, which are semantically annotated using the
KIM knowledge management platform. A web interface then
allows conceptual search and browsing of news stories, and
playing of the parts of the media files corresponding to each news
story. The use of material from the World Wide Web allows much
higher quality textual descriptions and semantic annotations to be
produced than would have been possible using the ASR transcript
directly. The semantic annotations can form a part of the Semantic
Web, and an evaluation shows that the system operates with high
precision, and with a moderate level of recall.},
added-at = {2009-07-13T10:40:00.000+0200},
address = {Chiba, Japan},
author = {Dowman, M. and Tablan, V. and Cunningham, H. and Popov, B.},
biburl = {https://www.bibsonomy.org/bibtex/2d123fa0113a47fc4a5f0ce510757d7e3/casi},
booktitle = {Proceedings of the 14th International World Wide Web Conference},
interhash = {fc03761e6f3030f2d0b0a8b3f3478276},
intrahash = {d123fa0113a47fc4a5f0ce510757d7e3},
keywords = {annotation multimedia news news-video-event-paper phd retrieval thesis-semantic-multimedia video web},
note = {{\small {\tt http://gate.ac.uk/sale/www05/web-assisted-annotation.pdf}}},
timestamp = {2009-07-13T10:40:00.000+0200},
title = {Web-Assisted Annotation, Semantic Indexing and Search of Television and Radio News},
year = 2005
}