A systematic comparison of various statistical alignment models
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Semi-supervised training for statistical word alignment
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Measuring Word Alignment Quality for Statistical Machine Translation
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A comparison of merging strategies for translation of German compounds
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Effects of morphological analysis in translation between German and English
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StatMT '09 Proceedings of the Fourth Workshop on Statistical Machine Translation
Vs and OOVs: two problems for translation between German and English
WMT '10 Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR
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We describe the LIU systems for English-German and German-English translation in the WMT09 shared task. We focus on two methods to improve the word alignment: (i) by applying Giza++ in a second phase to a reordered training corpus, where reordering is based on the alignments from the first phase, and (ii) by adding lexical data obtained as high-precision alignments from a different word aligner. These methods were studied in the context of a system that uses compound processing, a morphological sequence model for German, and a part-of-speech sequence model for English. Both methods gave some improvements to translation quality as measured by Bleu and Meteor scores, though not consistently. All systems used both out-of-domain and in-domain data as the mixed corpus had better scores in the baseline configuration.