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.
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References
L. R. Bahl, F. Jelinek, and R. L. Mercer. A maximum likelihood approach to continuous speech recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 5(2):179–190, 1983.
J. Barnett, S. Anderson, J. Broglio, M. Singh, R. Hudson, and S. W. Kuo. Experiments in spoken queries for document retrieval. In Proceedings of Eurospeech97, pages 1323–1326, 1997.
F. Crestani. Word recognition errors and relevance feedback in spoken query processing. In Proceedings of the Fourth International Conference on Flexible Query Answering Systems, pages 267–281, 2000.
J. S. Garofolo, E. M. Voorhees, V. M. Stanford, and K. S. Jones. TREC-6 1997 spoken document retrieval track overview and results. In Proceedings of the 6th Text REtrieval Conference, pages 83–91, 1997.
S. Johnson, P. Jourlin, G. Moore, K. S. Jones, and P. Woodland. The Cambridge University spoken document retrieval system. In Proceedings of ICASSP’99, pages 49–52, 1999.
G. Jones, J. Foote, K. S. Jones, and S. Young. Retrieving spoken documents by combining multiple index sources. In Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 30–38, 1996.
T. Kawahara, A. Lee, T. Kobayashi, K. Takeda, N. Minematsu, S. Sagayama, K. Itou, A. Ito, M. Yamamoto, A. Yamada, T. Utsuro, and K. Shikano. Free software toolkit for Japanese large vocabulary continuous speech recognition. In Proceedings of the 6th International Conference on Spoken Language Processing, pages 476–479, 2000.
K. Kwok and M. Chan. Improving two-stage ad-hoc retrieval for short queries. In Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 250–256, 1998.
H. Masataki, Y. Sagisaka, K. Hisaki, and T. Kawahara. Task adaptation using MAP estimation in n-gram language modeling. In Proceedings of ICASSP’97, pages 783–786, 1997.
Y. Matsumoto, A. Kitauchi, T. Yamashita, Y. Hirano, H. Matsuda, and M. Asahara. Japanese morphological analysis system ChaSen version 2.0 manual 2nd edition. Technical Report NAIST-IS-TR99009, NAIST, 1999.
National Institute of Informatics. Proceedings of the 2nd NTCIR Workshop Meeting on Evaluation of Chinese & Japanese Text Retrieval and Text Summarization, 2001.
S. Robertson and S. Walker. Some simple effective approximations to the 2-poisson model for probabilistic weighted retrieval. In Proceedings of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 232–241, 1994.
K. Seymore and R. Rosenfeld. Using story topics for language model adaptation. In Proceedings of Eurospeech97, 1997.
P. Sheridan, M. Wechsler, and P. Schäuble. Cross-language speech retrieval: Establishing a baseline performance. In Proceedings of the 20th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 99–108, 1997.
A. Singhal and F. Pereira. Document expansion for speech retrieval. In Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 34–41, 1999.
S. Srinivasan and D. Petkovic. Phonetic confusion matrix based spoken document retrieval. In Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 81–87, 2000.
E. M. Voorhees. Variations in relevance judgments and the measurement of retrieval effectiveness. In Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 315–323, 1998.
M. Wechsler, E. Munteanu, and P. Schäuble. New techniques for open-vocabulary spoken document retrieval. In Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 20–27, 1998.
S. Whittaker, J. Hirschberg, J. Choi, D. Hindle, F. Pereira, and A. Singhal. SCAN: Designing and evaluating user interfaces to support retrieval from speech archives. In Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 26–33, 1999.
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Fujii, A., Itou, K., Ishikawa, T. (2002). Speech-Driven Text Retrieval: Using Target IR Collections for Statistical Language Model Adaptation in Speech Recognition. In: Coden, A.R., Brown, E.W., Srinivasan, S. (eds) Information Retrieval Techniques for Speech Applications. IRTSA 2001. Lecture Notes in Computer Science, vol 2273. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45637-6_9
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DOI: https://doi.org/10.1007/3-540-45637-6_9
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