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Morphological Inflection Generation Using Character Sequence to Sequence Learning

2015-12-18NAACL 2016Code Available0· sign in to hype

Manaal Faruqui, Yulia Tsvetkov, Graham Neubig, Chris Dyer

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Abstract

Morphological inflection generation is the task of generating the inflected form of a given lemma corresponding to a particular linguistic transformation. We model the problem of inflection generation as a character sequence to sequence learning problem and present a variant of the neural encoder-decoder model for solving it. Our model is language independent and can be trained in both supervised and semi-supervised settings. We evaluate our system on seven datasets of morphologically rich languages and achieve either better or comparable results to existing state-of-the-art models of inflection generation.

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