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Abstract / Description of output
Different machine translation engines can be remarkably dissimilar not only with respect to their technical paradigm, but also with respect to the translation output they yield. System combination is a method for combining the output of multiple machine translation engines in order to take benefit of the strengths of each of the individual engines.
In this work we introduce a novel system combination implementation which is integrated into Jane, RWTH’s open source statistical machine translation toolkit. On the most recent Workshop on Statistical Machine Translation system combination shared task, we achieve improvements of up to 0.7 points in BLEU over the best system combination hypotheses which were submitted for the official evaluation. Moreover, we enhance our system combination pipeline with additional n-gram language models and lexical translation models.
In this work we introduce a novel system combination implementation which is integrated into Jane, RWTH’s open source statistical machine translation toolkit. On the most recent Workshop on Statistical Machine Translation system combination shared task, we achieve improvements of up to 0.7 points in BLEU over the best system combination hypotheses which were submitted for the official evaluation. Moreover, we enhance our system combination pipeline with additional n-gram language models and lexical translation models.
Original language | English |
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Title of host publication | Proceedings of the Demonstrations at the 14th Conference of the European Chapter of the Association for Computational Linguistics |
Place of Publication | Gothenburg, Sweden |
Publisher | Association for Computational Linguistics |
Pages | 29-32 |
Number of pages | 4 |
Publication status | Published - 1 Apr 2014 |
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