A syntactic language model based on incremental CCG parsing
Hassan, Hany, Sima'an, Khalil and Way, AndyORCID: 0000-0001-5736-5930
(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
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.