Aziz, W., Dymetman, M. and Specia, L. orcid.org/0000-0002-5495-3128 (2014) Exact decoding for phrase-based statistical machine translation. In: EMNLP 2014 - 2014 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference. EMNLP 2014: Conference on Empirical Methods in Natural Language Processing, 25th –29th October 2014, Doha, Qatar. , pp. 1237-1249. ISBN 9781937284961
Abstract
© 2014 Association for Computational Linguistics. The combinatorial space of translation derivations in phrase-based statistical machine translation is given by the intersection between a translation lattice and a target language model. We replace this intractable intersection by a tractable relaxation which incorporates a low-order upperbound on the language model. Exact optimisation is achieved through a coarseto- fine strategy with connections to adaptive rejection sampling. We perform exact optimisation with unpruned language models of order 3 to 5 and show searcherror curves for beam search and cube pruning on standard test sets. This is the first work to tractably tackle exact optimisation with language models of orders higher than 3.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | ACL materials are Copyright (C) 1963-2016 ACL; other materials are copyrighted by their respective copyright holders. Material prior to 2016 is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License (http://creativecommons.org/licenses/by-nc-sa/3.0/). Permission is granted to make copies for the purposes of teaching and research. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 25 Aug 2016 09:24 |
Last Modified: | 25 Oct 2016 01:12 |
Status: | Published |
Refereed: | Yes |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:97984 |