Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Translating collocations for bilingual lexicons: a statistical approach
Computational Linguistics
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Phrase-Based Statistical Machine Translation
KI '02 Proceedings of the 25th Annual German Conference on AI: Advances in Artificial Intelligence
A systematic comparison of various statistical alignment models
Computational Linguistics
Population-Based Incremental Learning: A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning
Models of translational equivalence among words
Computational Linguistics
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
A polynomial-time algorithm for statistical machine translation
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
A comparison of alignment models for statistical machine translation
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Inducing multilingual text analysis tools via robust projection across aligned corpora
HLT '01 Proceedings of the first international conference on Human language technology research
Fast decoding and optimal decoding for machine translation
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Statistical phrase-based translation
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Minimally supervised morphological analysis by multimodal alignment
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Improved statistical alignment models
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
The Candide system for machine translation
HLT '94 Proceedings of the workshop on Human Language Technology
WWSM '00 Proceedings of the ACL-2000 workshop on Word senses and multi-linguality - Volume 8
An efficient A* search algorithm for statistical machine translation
DMMT '01 Proceedings of the workshop on Data-driven methods in machine translation - Volume 14
A phrase-based, joint probability model for statistical machine translation
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
An evaluation exercise for word alignment
HLT-NAACL-PARALLEL '03 Proceedings of the HLT-NAACL 2003 Workshop on Building and using parallel texts: data driven machine translation and beyond - Volume 3
The equation for response to selection and its use for prediction
Evolutionary Computation
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In statistical machine translation, an alignment defines a mapping between the words in the source and in the target sentence. Alignments are used, on the one hand, to train the statistical models and, on the other, during the decoding process to link the words in the source sentence to the words in the partial hypotheses generated. In both cases, the quality of the alignments is crucial for the success of the translation process. In this paper, we propose several evolutionary algorithms for computing alignments between two sentences in a parallel corpus. This algorithm has been tested on different tasks involving different pair of languages. Specifically, in the two shared tasks proposed in the HLT-NAACL 2003 and in the ACL 2005, the EDA-based algorithm outperforms the best participant systems. In addition, the experiments show that, because of the limitations of the well known statistical alignment models, new improvements in alignments quality could not be achieved by using improved search algorithms only.