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
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We recently decided to develop a new alignment algorithm for the purpose of improving our Example-Based Machine Translation (EBMT) system's performance, since subsentential alignment is critical in locating the correct translation for a matched fragment of the input. Unlike most algorithms in the literature, this new Symmetric Probabilistic Alignment (SPA) algorithm treats the source and target languages in a symmetric fashion. In this short paper, we outline our basic algorithm and some extensions for using context and positional information, and compare its alignment accuracy on the Romanian-English data for the shared task with IBM Model 4 and the reported results from the prior workshop.