DocumentCode :
2924448
Title :
Indexing and search of multimodal information
Author :
Hauptmann, Alexander G. ; Wactlar, Howard D.
Author_Institution :
Sch. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA
Volume :
1
fYear :
1997
fDate :
21-24 Apr 1997
Firstpage :
195
Abstract :
The Informedia Digital Library Project allows full content indexing and retrieval of text, audio and video material. The integration of speech recognition, image processing, natural language processing and information retrieval overcomes limits in each technology to create a useful system. In order to answer the question how good speech recognition has to be in order to be useful and usable for indexing and retrieving speech recognizer generated transcripts, some empirical evidence is presented that illustrates the degradation of information retrieval at different levels of speech accuracy. In our experiments, word error rates up to 25% did not significantly impact information retrieval and error rates of 50% still provided 85 to 95% of the recall and precision relative to fully accurate transcripts in the same retrieval system
Keywords :
image processing; information retrieval systems; multimedia computing; natural languages; speech recognition; Informedia Digital Library Project; audio material; image processing; information retrieval; multimodal information; natural language processing; speech recognition; speech recognizer generated transcripts; text; video material; Content based retrieval; Degradation; Error analysis; Image processing; Image retrieval; Indexing; Information retrieval; Natural language processing; Software libraries; Speech recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on
Conference_Location :
Munich
ISSN :
1520-6149
Print_ISBN :
0-8186-7919-0
Type :
conf
DOI :
10.1109/ICASSP.1997.599599
Filename :
599599
Link To Document :
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