8 research outputs found

    Combination of Machine Translation Systems via Hypothesis Selection from Combined n-best lists

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    Different approaches in machine translation achieve similar translation quality with a variety of translations in the output. Recently it has been shown, that it is possible to leverage the individual strengths of various systems and improve the overall translation quality by combining translation outputs. In this paper we present a method of hypothesis selection which is relatively simple compared to system combination methods which construct a synthesis of the input hypotheses. Our method uses information from n-best lists from several MT systems and features on the sentence level which are independent from the MT systems involved to improve the translation quality

    Recent improvements in the CMU large-scale Chinese-English SMT system

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    In this paper we describe recent improvements to components and methods used in our statistical machine translation system for Chinese-English used in the January 2008 GALE evaluation. Main improvements are results of consistent data processing, larger statistical models and a POS-based word reordering approach

    CMU system combination for WMT’09

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    This paper describes the CMU entry for the system combination shared task at WMT’09. Our combination method is hypothesis selection, which uses information from n-best lists from several MT systems. The sentence level features are independent from the MT systems involved. To compensate for various n-best list sizes in the workshop shared task including firstbest-only entries, we normalize one of our high-impact features for varying sub-list size. We combined restricted data trac

    Recent Improvements in the CMU Large Scale Chinese-English SMT System

    No full text
    In this paper we describe recent improvements to components and methods used in our statistical machine translation system for Chinese-English used in the January 2008 GALE evaluation. Main improvements are results of consistent data processing, larger statistical models and a POS-based word reordering approach
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