SpeechDriven Text Retrieval: Using Target IR
Collections for Statistical Language Model
Adaptation in Speech Recognition

Atsushi Fujii 1 , Katunobu Itou 2 , and Tetsuya Ishikawa 1
1 University of Library and Information Science
12 Kasuga, Tsukuba, 3058550, Japan
{fujii,ishikawa}@ulis.ac.jp
2 National Institute of Advanced Industrial Science and Technology
111 Chuuou Daini Umezono, Tsukuba, 3058568, Japan
itou@ni.aist.go.jp

Abstract. Speech recognition has of late become a practical technology 
for real world applications. Aiming at speechdriven 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.

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