Opening Statistical Translation Engines to Terminological Resources
NLDB '02 Proceedings of the 6th International Conference on Applications of Natural Language to Information Systems-Revised Papers
What's Been Forgotten in Translation Memory
AMTA '00 Proceedings of the 4th Conference of the Association for Machine Translation in the Americas on Envisioning Machine Translation in the Information Future
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
A DP based search algorithm for statistical machine translation
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Example-Based Machine Translation in the Pangloss system
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Towards a unified approach to memory- and statistical-based machine translation
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Shallow parsing as part-of-speech tagging
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
EPIA '09 Proceedings of the 14th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence
CICLing'08 Proceedings of the 9th international conference on Computational linguistics and intelligent text processing
Panning for EBMT gold, or "Remembering not to forget"
Machine Translation
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Despite the exciting work accomplished over the past decade in the field of Statistical Machine Translation (SMT), we are still far from the point of being able to say that machine translation fully meets the needs of real-life users. In a previous study [6], we have shown how a SMT engine could benefit from terminological resources, especially when translating texts very different from those used to train the system. In the present paper, we discuss the opening of SMT to examples automatically extracted from a Translation Memory (TM). We report results on a fair-sized translation task using the database of a commercial bilingual concordancer.