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Programming Language Techniques for Natural Language Applications

Abstract
It is easy to imagine machines that can communicate in natural language. Constructing such machines is more difficult. The aim of this thesis is to demonstrate how declarative grammar formalisms that distinguish between abstract and concrete syntax make it easier to develop natural language applications. We describe how the type-theorectical grammar formalism Grammatical Framework (GF) can be used as a high-level language for natural language applications. By taking advantage of techniques from the field of programming language implementation, we can use GF grammars to perform portable and efficient parsing and linearization, generate speech recognition language models, implement multimodal fusion and fission, generate support code for abstract syntax transformations, generate dialogue managers, and implement speech translators and web-based syntax-aware editors. By generating application components from a declarative grammar, we can reduce duplicated work, ensure consistency, make it easier to build multilingual systems, improve linguistic quality, enable re-use across system domains, and make systems more portable.
Degree
Doctor of Engineering
University
University of Gothenburg. IT-Faculty & Chalmers University of Technology
Institution
Department of Computer Science and Engineering
Disputation
Onsdagen den 12 november, kl. 10.15. Lokal EF, Hörsalsvägen 11, Chalmers University of Technology
Date of defence
2008-11-12
E-mail
bjorn@bringert.net
URI
http://hdl.handle.net/2077/18350
Collections
  • Doctoral Theses / Doktorsavhandlingar Institutionen för data- och informationsteknik
  • Doctoral Theses from University of Gothenburg / Doktorsavhandlingar från Göteborgs universitet
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gupea_2077_18350_1.pdf (2.134Mb)
Date
2008-10-16
Author
Bringert, Björn
Publication type
Doctoral thesis
ISBN
978-91-628-7618-0
ISSN
1653-1787
Series/Report no.
Technical report. D / Department of Computer Science and Engineering, Language Technology Research Group
48
Language
eng
Metadata
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