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INTERSPEECH 2007 Classification of Discourse Functions of Affirmative Words in Spoken Dialogue (2009)

Abstract
We present results of a series of machine learning experiments that address the classification of the discourse function of single affirmative cue words such as alright, okay and mm-hm in a spoken dialogue corpus. We suggest that a simple discourse/sentential distinction is not sufficient for such words and propose two additional classification sub-tasks: identifying (a) whether such words convey acknowledgment or agreement, and (b) whether they cue the beginning or end of a discourse segment. We also study the classification of each individual word into its most common discourse functions. We show that models based on contextual features extracted from the time-aligned transcripts approach the error rate of trained human aligners. Index Terms: cue words, discourse markers, spoken dialogue systems.

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Download http://citeseerx.ist.psu.edu/viewdoc/summary?doi=?doi=10.1.1.137.8793
Source http://www.cs.columbia.edu/~sbenus/Research/Gravano_et_al_dms_IS07.PDF
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Type text
Language English
Relation 10.1.1.14.9528, 10.1.1.50.8204, 10.1.1.47.5102, 10.1.1.14.1020, 10.1.1.14.4612, 10.1.1.94.6748