Papers › Morphological Inflection Generation Using Character Sequence to Sequence Learning
Morphological Inflection Generation Using Character Sequence to Sequence Learning
Manaal Faruqui, Yulia Tsvetkov, Graham Neubig, Chris Dyer
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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