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A syntactic language model based on incremental CCG parsing

Hassan, Hany and Sima'an, Khalil and Way, Andy (2008) A syntactic language model based on incremental CCG parsing. In: SLT 2008 - 2nd IEEE Spoken Language Technology Workshop, 15-19 December 2008 , Goa, India. ISBN 978-1-4244-3471-8

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Syntactically-enriched language models (parsers) constitute a promising component in applications such as machine translation and speech-recognition. To maintain a useful level of accuracy, existing parsers are non-incremental and must span a combinatorially growing space of possible structures as every input word is processed. This prohibits their incorporation into standard linear-time decoders. In this paper, we present an incremental, linear-time dependency parser based on Combinatory Categorial Grammar (CCG) and classification techniques. We devise a deterministic transform of CCGbank canonical derivations into incremental ones, and train our parser on this data. We discover that a cascaded, incremental version provides an appealing balance between efficiency and accuracy.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Next Generation Localisation (CNGL)
Publisher:Institute of Electrical and Electronics Engineers
Official URL:
Copyright Information:©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Funders:Science Foundation Ireland
ID Code:15817
Deposited On:23 Nov 2010 16:21 by Shane Harper. Last Modified 23 Nov 2010 16:21

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