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Rule filtering by pattern for efficient hierarchical translation
- In Proceedings of the EACL
, 2009
"... We describe refinements to hierarchical translation search procedures intended to reduce both search errors and memory usage through modifications to hypothesis expansion in cube pruning and reductions in the size of the rule sets used in translation. Rules are put into syntactic classes based on th ..."
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Cited by 6 (1 self)
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We describe refinements to hierarchical translation search procedures intended to reduce both search errors and memory usage through modifications to hypothesis expansion in cube pruning and reductions in the size of the rule sets used in translation. Rules are put into syntactic classes based on the number of non-terminals and the pattern, and various filtering strategies are then applied to assess the impact on translation speed and quality. Results are reported on the 2008 NIST Arabic-to-English evaluation task. 1
Exact Decoding of Phrase-based Translation Models through Lagrangian Relaxation
- In To appear proc. of EMNLP
, 2011
"... This paper describes an algorithm for exact decoding of phrase-based translation models, based on Lagrangian relaxation. The method recovers exact solutions, with certificates of optimality, on over 99 % of test examples. The method is much more efficient than approaches based on linear programming ..."
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Cited by 4 (1 self)
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This paper describes an algorithm for exact decoding of phrase-based translation models, based on Lagrangian relaxation. The method recovers exact solutions, with certificates of optimality, on over 99 % of test examples. The method is much more efficient than approaches based on linear programming (LP) or integer linear programming (ILP) solvers: these methods are not feasible for anything other than short sentences. We compare our method to MOSES (Koehn et al., 2007), and give precise estimates of the number and magnitude of search errors that MOSES makes.
Lattice Rescoring Methods for Statistical Machine Translation
"... This dissertation is the result of my own work and includes nothing which is the outcome of work done in collaboration except where specifically indicated in the text. It has not been submitted in whole or in part for a degree at any other university. Some of the work has been published previously i ..."
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This dissertation is the result of my own work and includes nothing which is the outcome of work done in collaboration except where specifically indicated in the text. It has not been submitted in whole or in part for a degree at any other university. Some of the work has been published previously in conference proceedings (Blackwood et al., 2008a; Blackwood
Stochastic K-TSS bi-languages for Machine Translation
"... One of the approaches to statistical machine translation is based on joint probability distributions over some source and target languages. In this work we propose to model the joint probability distribution by stochastic regular bi-languages. Specifically we introduce the stochastic k-testable in t ..."
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One of the approaches to statistical machine translation is based on joint probability distributions over some source and target languages. In this work we propose to model the joint probability distribution by stochastic regular bi-languages. Specifically we introduce the stochastic k-testable in the strict sense bi-languages to represent the joint probability distribution of source and target languages. With this basis we present a reformulation of the GIATI methodology to infer stochastic regular bi-languages for machine translation purposes. 1
Alignment Models and Algorithms for Statistical Machine Translation
, 2010
"... This degree is submitted to the University of Cambridge ..."
