• DocumentCode
    2971569
  • Title

    Any questions? Automatic question detection in meetings

  • Author

    Boakye, Kofi ; Favre, Benoit ; Hakkani-Tür, Dilek

  • Author_Institution
    Int. Comput. Sci. Inst., Berkeley, CA, USA
  • fYear
    2009
  • fDate
    Nov. 13 2009-Dec. 17 2009
  • Firstpage
    485
  • Lastpage
    489
  • Abstract
    In this paper, we describe our efforts toward the automatic detection of English questions in meetings. We analyze the utility of various features for this task, originating from three distinct classes: lexico-syntactic, turn-related, and pitch-related. Of particular interest is the use of parse tree information in classification, an approach as yet unexplored. Results from experiments on the ICSI MRDA corpus demonstrate that lexico-syntactic features are most useful for this task, with turn-and pitch-related features providing complementary information in combination. In addition, experiments using reference parse trees on the broadcast conversation portion of the OntoNotes release 2.9 data set illustrate the potential of parse trees to outperform word lexical features.
  • Keywords
    natural language processing; pattern classification; speech processing; ICSI MRDA corpus; OntoNotes; automatic question detection; broadcast conversation portion; lexico-syntactic features; parse tree information; reference parse trees; Broadcasting; Classification tree analysis; Computer science; Computer vision; Humans; Indexing; Natural languages;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automatic Speech Recognition & Understanding, 2009. ASRU 2009. IEEE Workshop on
  • Conference_Location
    Merano
  • Print_ISBN
    978-1-4244-5478-5
  • Electronic_ISBN
    978-1-4244-5479-2
  • Type

    conf

  • DOI
    10.1109/ASRU.2009.5373293
  • Filename
    5373293