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Modèles de traduction évolutifs

Abstract : Although machine translation research achieved big progress for several years, the output of an automated system cannot be published without prior revision by human annotators. Based on this fact, we wanted to exploit the user feedbacks from the review process in order to incrementally adapt our statistical system over time.As part of this thesis, we are therefore interested in the post-editing, one of the most active fields of research, and what is more widely used in the translation and localization industry.However, the integration of user feedbacks is not an obvious task. On the one hand, we must be able to identify the information that will be useful for the system, among all changes made by the user. To address this problem, we introduced a new concept (the “Post-Editing Actions”), and proposed an analysis methodology for automatic identification of this information from post-edited data. On the other hand, for the continuous integration of user feedbacks, we havedeveloped an algorithm for incremental adaptation of a statistical machine translation system, which gets higher performance than the standard procedure. This is even more interesting as both development and optimization of this type of translation system has a very computational cost, sometimes requiring several days of computing.Conducted jointly with SYSTRAN and LIUM, the research work of this thesis is part of the French Government Research Agency project COSMAT 2. This project aimed to provide a collaborative machine translation service for scientific content to the scientific community. The collaborative aspect of this service with the possibility for users to review the translations givesan application framework for our research.
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  • HAL Id : tel-01142926, version 1


Frédéric Blain. Modèles de traduction évolutifs. Ordinateur et société [cs.CY]. Université du Maine, 2013. Français. ⟨NNT : 2013LEMA1034⟩. ⟨tel-01142926⟩



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