In this paper we present new research in translation assistance. We describe a system capable of translating native language (L1) fragments to foreign language (L2) fragments in an L2 context. Practical applications of this research can be framed in the context of second language learning. The type of translation assistance system under investigation here encourages language learners to write in their target language while allowing them to fall back to their native language in case the correct word or expression is not known. These code switches are subsequently translated to L2 given the L2 context. We study the feasibility of exploiting cross-lingual context to obtain high-quality translation suggestions that improve over statistical language modelling and word-sense disambiguation baselines. A classification-based approach is presented that is indeed found to improve significantly over these baselines by making use of a contextual window spanning a small number of neighbouring words
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