Cross-lingual, Character-Level Neural Morphological Tagging

• URL: http://arxiv.org/abs/1708.09157v5
• Date: Thu, 6 Jun 2024 08:27:54 GMT
• Title: Cross-lingual, Character-Level Neural Morphological Tagging
• Authors: Ryan Cotterell, Georg Heigold,
• Abstract summary: 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.
• Score: 57.0020906265213
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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