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arXiv · 1512.06110

Morphological Inflection Generation Using Character Sequence to Sequence Learning

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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Manaal Faruqui, Yulia Tsvetkov, Graham Neubig, Chris Dyer. 2015-12-18. Morphological Inflection Generation Using Character Sequence to Sequence Learning. https://arxiv.org/abs/1512.06110

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