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

  • Authors:
  • Atsushi Fujii;Katunobu Itou;Tetsuya Ishikawa

  • Affiliations:
  • -;-;-

  • Venue:
  • Information Retrieval Techniques for Speech Applications [this book is based on the workshop “Information Retrieval Techniques for Speech Applications”, held as part of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in New Orleans, USA, in September 2001].
  • Year:
  • 2001

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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.