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Speech Repairs, Intonational Phrases and Discourse Markers: Modeling Speakers'
 

Summary: Speech Repairs, Intonational Phrases and
Discourse Markers: Modeling Speakers'
Utterances in Spoken Dialogue
Peter A. Heeman James F. Alleny
Oregon Graduate Institute University of Rochester
Interactive spoken dialogue provides many new challenges for natural language understanding
systems. One of the most critical challenges is simply determining the speaker's intended utter-
ances: both segmenting a speaker's turn into utterances and determining the intended words in
each utterance. Even assuming perfect word recognition, the latter problem is complicated by the
occurrence of speech repairs, which occur where speakers go back and change (or repeat) some-
thing they just said. The words that are replaced or repeated are no longer part of the intended
utterance, and so need to be identified. Segmenting turns and resolving repairs are strongly
intertwined with a third task: identifying discourse markers. Because of the interactions, and
interactions with POS tagging and speech recognition, we need to address these tasks together
and early on in the processing stream. This paper presents a statistical language model in which
we redefine the speech recognition problem so that it includes the identification of POS tags,
discourse markers, speech repairs and intonational phrases. By solving these simultaneously, we
obtain better results on each task than addressing them separately. Our model is able to identify
72% of turn-internal intonational boundaries with a precision of 71%, 97% of discourse markers
with 96% precision, and detect and correct 66% of repairs with 74% precision.

  

Source: Allen, James F. - Department of Computer Science, University of Rochester

 

Collections: Computer Technologies and Information Sciences