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Deep open-source machine translation

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Machine Translation

Abstract

This paper summarizes ongoing efforts to provide software infrastructure (and methodology) for open-source machine translation that combines a deep semantic transfer approach with advanced stochastic models. The resulting infrastructure combines precise grammars for parsing and generation, a semantic-transfer based translation engine and stochastic controllers. We provide both a qualitative and quantitative experience report from instantiating our general architecture for Japanese–English MT using only open-source components, including HPSG-based grammars of English and Japanese.

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Correspondence to Francis Bond.

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Bond, F., Oepen, S., Nichols, E. et al. Deep open-source machine translation. Machine Translation 25, 87–105 (2011). https://doi.org/10.1007/s10590-011-9099-4

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