Any questions? Automatic question detection in meetings

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationProceedings of the 2009 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2009
Pages485-489
Number of pages5
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2009 - Merano, Italy
Duration: Dec 13 2009Dec 17 2009

Publication series

NameProceedings of the 2009 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2009

Other

Other2009 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2009
Country/TerritoryItaly
CityMerano
Period12/13/0912/17/09

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Signal Processing

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