Date of Original Version

9-2013

Type

Article

Journal Title

Prague Journal of Mathematical Linguistics

Volume

100

Issue

1

First Page

51

Last Page

62

Rights Management

© 2013 PBML

Abstract or Description

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.

DOI

10.2478/pralin-2013-0011

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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Published In

Prague Journal of Mathematical Linguistics, 100, 1, 51-62.