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        <title>Joint Incremental Disfluency Detection and Dependency Parsing</title>
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    <abstract>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.</abstract>
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    <identifier type="doi">10.1162/tacl_a_00171</identifier>
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%0 Journal Article
%T Joint Incremental Disfluency Detection and Dependency Parsing
%A Honnibal, Matthew
%A Johnson, Mark
%J Transactions of the Association for Computational Linguistics
%D 2014
%V 2
%I MIT Press
%C Cambridge, MA
%F honnibal-johnson-2014-joint
%X 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.
%R 10.1162/tacl_a_00171
%U https://aclanthology.org/Q14-1011/
%U https://doi.org/10.1162/tacl_a_00171
%P 131-142

Markdown (Informal)

[Joint Incremental Disfluency Detection and Dependency Parsing](https://aclanthology.org/Q14-1011/) (Honnibal & Johnson, TACL 2014)

• Joint Incremental Disfluency Detection and Dependency Parsing (Honnibal & Johnson, TACL 2014)

ACL

• Matthew Honnibal and Mark Johnson. 2014. Joint Incremental Disfluency Detection and Dependency Parsing. Transactions of the Association for Computational Linguistics, 2:131–142.