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arXiv · 1708.09157

Cross-lingual, Character-Level Neural Morphological Tagging

Ryan Cotterell·Georg Heigold
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Abstract

Even for common NLP tasks, sufficient supervision is not available in many languages -- morphological tagging is no exception. In the work presented here, we explore a transfer learning scheme, whereby we train character-level recurrent neural taggers to predict morphological taggings for high-resource languages and low-resource languages together. Learning joint character representations among multiple related languages successfully enables knowledge transfer from the high-resource languages to the low-resource ones, improving accuracy by up to 30% over a monolingual model.

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Ryan Cotterell, Georg Heigold. 2017-08-30. Cross-lingual, Character-Level Neural Morphological Tagging. https://doi.org/10.18653/v1%2Fd17-1078

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