Title
Speech-Driven Text Retrieval: Using Target IR Collections for Statistical Language Model Adaptation in Speech Recognition
Abstract
Speech recognition has of late become a practical technology for real world applications. Aiming at speech-driven text retrieval, which facilitates retrieving information with spoken queries, we propose a method to integrate speech recognition and retrieval methods. Since users speak contents related to a target collection, we adapt statistical language models used for speech recognition based on the target collection, so as to improve both the recognition and retrieval accuracy. Experiments using existing test collections combined with dictated queries showed the effectiveness of our method.
Year
DOI
Venue
2001
10.1007/3-540-45637-6_9
Research and Development in Information Retrieval
Keywords
DocType
Volume
retrieval accuracy,practical technology,target ir collections,real world application,statistical language model,target collection,speech recognition,existing test collection,statistical language model adaptation,retrieval method,speech-driven text retrieval
Conference
cs.CL/0206037
ISSN
ISBN
Citations 
Anni R. Coden and Eric W. Brown and Savitha Srinivasan (Eds.), Information Retrieval Techniques for Speech Applications (LNCS 2273), pp.94-104, Springer, 2002
3-540-43156-X
16
PageRank 
References 
Authors
1.43
16
3
Name
Order
Citations
PageRank
Atsushi Fujii148659.25
Katunobu Itou231944.36
Tetsuya Ishikawa322630.46