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