Type

Conference Proceedings

Authors

Andy Way
Khalil Sima'an
Hany Hassan

Subjects

Linguistics

Topics
classification techniques language parsing language models machine translating speech recognition ccg machine translation combinatory categorial grammar

A syntactic language model based on incremental CCG parsing (2008)

Abstract 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.
Collections Ireland -> Dublin City University -> Publication Type = Conference or Workshop Item
Ireland -> Dublin City University -> Subject = Computer Science
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: Centre for Next Generation Localisation (CNGL)
Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> Subject = Computer Science: Machine translating
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres

Full list of authors on original publication

Andy Way, Khalil Sima'an, Hany Hassan

Experts in our system

1
Andy Way
Dublin City University
Total Publications: 229
 
2
Khalil Sima'an
Dublin City University
Total Publications: 7