Joint Incremental Disfluency Detection and Dependency Parsing
2014 ◽
Vol 2
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pp. 131-142
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Keyword(s):
We present an incremental dependency parsing model that jointly performs disfluency detection. The model handles speech repairs using a novel non-monotonic transition system, and includes several novel classes of features. For comparison, we evaluated two pipeline systems, using state-of-the-art disfluency detectors. The joint model performed better on both tasks, with a parse accuracy of 90.5% and 84.0% accuracy at disfluency detection. The model runs in expected linear time, and processes over 550 tokens a second.
Keyword(s):
2021 ◽
Vol 12
(5)
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pp. 1-21
2020 ◽
Vol 34
(05)
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pp. 8319-8326
Keyword(s):
2013 ◽
Vol 1
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pp. 301-314
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Keyword(s):
2020 ◽
Vol 34
(04)
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pp. 4412-4419
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Keyword(s):
2008 ◽
Vol 18
(05)
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pp. 683-712
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