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This article describes the combination of a SYSTRAN system with a “statistical postediting” (SPE) system. We document qualitative analysis on two experiments performed in the shared task of the ACL 2007 Workshop on Statistical Machine Translation. Comparative results and more integrated “hybrid” techniques are discussed.
We describe here the two Systran/University of Edinburgh submissions for WMT2009. They involve a statistical post-editing model with a particular handling of named entities (English to French and German to English) and the extraction of phrasal rules (English to French).
This paper describes SYSTRAN submissions for the shared task of the third Workshop on Statistical Machine Translation at ACL. Our main contribution consists in a French-English statistical model trained without the use of any human-translated parallel corpus. In substitution, we translated a monolingual corpus with SYSTRAN rule-based translation engine to… (More)
A translation memory system attempts to retrieve useful suggestions from previous translations to assist a translator in a new translation task. While assisting the translator with a specific segment, some similarity metric is usually employed to select the best matches from previously translated segments to present to a translator. Automated methods for… (More)