Information retrieval from spoken documents

  • Authors:

  • Michal Fapšo;Pavel Smrž;Petr Schwarz;Igor Szöke;Milan Schwarz;Jan Černocký;Martin Karafiát;Lukáš Burget

  • Affiliations:

  • Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic;Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic;Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic;Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic;Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic;Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic;Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic;Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic

  • Venue:
  • CICLing'06 Proceedings of the 7th international conference on Computational Linguistics and Intelligent Text Processing
  • Year:
  • 2006

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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.