Carnegie Mellon University
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morphogen: Translation into Morphologically Rich Languages with Synthetic Phrases

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journal contribution
posted on 2013-09-01, 00:00 authored by Eva Schlinger, Victor Chahuneau, Chris Dyer

We present morphogen, a tool for improving translation into morphologically rich languages with synthetic phrases. We approach the problem of translating into morphologically rich languages in two phases. First, an inflection model is learned to predict target word inflections from source side context. Then this model is used to create additional sentence specific translation phrases. These “synthetic phrases” augment the standard translation grammars and decoding proceeds normally with a standard translation model. We present an open source Python implementation of our method, as well as a method of obtaining an unsupervised morphological analysis of the target language when no supervised analyzer is available.


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© 2013 PBML



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