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Overview of the CLEF-2005 Cross-Language Speech Retrieval Track

  • Ryen W. White
  • Douglas W. Oard
  • Gareth J. F. Jones
  • Dagobert Soergel
  • Xiaoli Huang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4022)

Abstract

The task for the CLEF-2005 cross-language speech retrieval track was to identify topically coherent segments of English interviews in a known-boundary condition. Seven teams participated, performing both monolingual and cross-language searches of ASR transcripts, automatically generated metadata, and manually generated metadata. Results indicate that monolingual search technology is sufficiently accurate to be useful for some purposes (the best mean average precision was 0.13) and cross-language searching yielded results typical of those seen in other applications (with the best systems approximating monolingual mean average precision).

Keywords

Average Precision Automatic Speech Recognition Test Collection Word Error Rate Relevance Judgment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ryen W. White
    • 1
  • Douglas W. Oard
    • 1
    • 2
  • Gareth J. F. Jones
    • 3
  • Dagobert Soergel
    • 2
  • Xiaoli Huang
    • 2
  1. 1.Institute for Advanced Computer Studies 
  2. 2.College of Information StudiesUniversity of MarylandCollege ParkUSA
  3. 3.School of ComputingDublin City UniversityIreland

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