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
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