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

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dc.creatorFujii, Atsushi
dc.creatorItou, Katunobu
dc.creatorIshikawa, Tetsuya
dc.date2002-06-24
dc.date.accessioned2026-07-07T03:18:33Z
dc.date.available2026-07-07T03:18:33Z
dc.descriptionSpeech 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.
dc.identifierhttps://arxiv.org/abs/cs/0206037
dc.identifierhttp://arxiv.org/abs/cs/0206037
dc.identifierAnni R. Coden and Eric W. Brown and Savitha Srinivasan (Eds.), Information Retrieval Techniques for Speech Applications (LNCS 2273), pp.94-104, Springer, 2002
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/31157
dc.subjectComputation and Language
dc.subjectI.2.7; H.3.3; H.5.1
dc.titleSpeech-Driven Text Retrieval: Using Target IR Collections for Statistical Language Model Adaptation in Speech Recognition
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