Semiring frameworks and algorithms for shortest-distance problems
Journal of Automata, Languages and Combinatorics
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
An end-to-end discriminative approach to machine translation
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Online large-margin training of syntactic and structural translation features
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Lattice Minimum Bayes-Risk decoding for statistical machine translation
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Complexity of finding the BLEU-optimal hypothesis in a confusion network
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Efficient extraction of oracle-best translations from hypergraphs
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
Comparing reordering constraints for SMT using efficient Bleu oracle computation
SSST '07 Proceedings of the NAACL-HLT 2007/AMTA Workshop on Syntax and Structure in Statistical Translation
Learning performance of a machine translation system: a statistical and computational analysis
StatMT '08 Proceedings of the Third Workshop on Statistical Machine Translation
A systematic analysis of translation model search spaces
StatMT '09 Proceedings of the Fourth Workshop on Statistical Machine Translation
OpenFst: a general and efficient weighted finite-state transducer library
CIAA'07 Proceedings of the 12th international conference on Implementation and application of automata
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
On dual decomposition and linear programming relaxations for natural language processing
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Assessing phrase-based translation models with oracle decoding
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Exact decoding of phrase-based translation models through Lagrangian relaxation
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Oracle decoding as a new way to analyze phrase-based machine translation
Machine Translation
Lattice BLEU oracles in machine translation
ACM Transactions on Speech and Language Processing (TSLP)
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The search space of Phrase-Based Statistical Machine Translation (PBSMT) systems can be represented under the form of a directed acyclic graph (lattice). The quality of this search space can thus be evaluated by computing the best achievable hypothesis in the lattice, the so-called oracle hypothesis. For common SMT metrics, this problem is however NP-hard and can only be solved using heuristics. In this work, we present two new methods for efficiently computing BLEU oracles on lattices: the first one is based on a linear approximation of the corpus BLEU score and is solved using the FST formalism; the second one relies on integer linear programming formulation and is solved directly and using the Lagrangian relaxation framework. These new decoders are positively evaluated and compared with several alternatives from the literature for three language pairs, using lattices produced by two PBSMT systems.