Abstract
This paper describes a designed and implemented system for efficient storage, indexing and search in collections of spoken documents that takes advantage of automatic speech recognition. As the quality of current speech recognizers is not sufficient for a great deal of applications, it is necessary to index the ambiguous output of the recognition, i. e. the acyclic graphs of word hypotheses — recognition lattices. Then, it is not possible to directly apply the standard methods known from text-based systems. The paper discusses an optimized indexing system for efficient search in the complex and large data structure that has been developed by our group. The search engine works as a server. The meeting browser JFerret, developed withing the European AMI project, is used as a client to browse search results.
This work was partly supported by European project AMI (Augmented Multi-party Interaction, FP6-506811) and Grant Agency of Czech Republic under project No. 102/05/0278. Pavel Smrž was supported by MŠMT Research Plan MSM 6383917201. The hardware used in this work was partially provided by CESNET under project No. 119/2004.
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© 2006 Springer-Verlag Berlin Heidelberg
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Fapšo, M. et al. (2006). Information Retrieval from Spoken Documents. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2006. Lecture Notes in Computer Science, vol 3878. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11671299_43
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DOI: https://doi.org/10.1007/11671299_43
Publisher Name: Springer, Berlin, Heidelberg
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