• DocumentCode
    3245681
  • Title

    Are extractive text summarisation techniques portable to broadcast news?

  • Author

    Christensen, Heidi ; Gotoh, Yoshihiko ; Kolluru, B. ; Renals, Steve

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Sheffield, UK
  • fYear
    2003
  • fDate
    30 Nov.-3 Dec. 2003
  • Firstpage
    489
  • Lastpage
    494
  • Abstract
    In this paper we report on a series of experiments which compare the effect of individual features on both text and speech summarisation, the effect of basing the speech summaries on automatic speech recognition transcripts with varying word error rates, and the effect of summarisation approach and transcript source on summary quality. We show that classical text summarisation features (based on stylistic and content information) are portable to broadcast news. However, the quality of the speech transcripts as well as the difference in information structure between broadcast and newspaper news affect the usability of the individual features.
  • Keywords
    error statistics; feature extraction; speech recognition; text analysis; automatic speech recognition transcripts; broadcast news; extractive text summarisation techniques; feature portability; summary quality; transcript source; varying word error rates; Automatic speech recognition; Computer science; Data mining; Error analysis; Knowledge transfer; Natural languages; Speech recognition; TV broadcasting; Text recognition; Usability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automatic Speech Recognition and Understanding, 2003. ASRU '03. 2003 IEEE Workshop on
  • Print_ISBN
    0-7803-7980-2
  • Type

    conf

  • DOI
    10.1109/ASRU.2003.1318489
  • Filename
    1318489