Language Modeling for Multi-Domain Speech-Driven Text Retrieval
Katunobu Itou, Atsushi Fujii, Tetsuya Ishikawa
Abstract
We report experimental results associated with speech-driven text retrieval, which facilitates retrieving information in multiple domains with spoken queries. Since users speak contents related to a target collection, we produce 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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