In this paper, we present the KIT systems participating in the Shared Translation Task translating between English↔German and English↔French. All translations are generated using phrase-based translation systems, using different kinds of word-based, part-ofspeech-based and cluster-based language models trained on the provided data. Additional models include bilingual language models, reordering models based on part-of-speech tags and syntactic parse trees, as well as a lexicalized reordering

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... el. In order to make use of noisy web-crawled data, we apply filtering and data selection methods for language modeling. A discriminative word lexicon using source context information proved beneficial for all translation directions.