2017
EMNLP
EMNLP 2017
A Sub-Character Architecture for Korean Language Processing
Abstract
AbstractWe introduce a novel sub-character architecture that exploits a unique compositional structure of the Korean language. Our method decomposes each character into a small set of primitive phonetic units called jamo letters from which character- and word-level representations are induced. The jamo letters divulge syntactic and semantic information that is difficult to access with conventional character-level units. They greatly alleviate the data sparsity problem, reducing the observation space to 1.6% of the original while increasing accuracy in our experiments. We apply our architecture to dependency parsing and achieve dramatic improvement over strong lexical baselines.
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Interdisciplinary Bridge
— Artificial Intelligence and Interdisciplinary and Machine Learning and Natural Language Processing
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Keyword Pioneer
— korean language
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Hot Topic Early Bird
— morphological analysis
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio
Authors
Topics
Machine Learning > Core Methods > Representation Learning
Natural Language Processing > Understanding > Syntax
Natural Language Processing > Resources & Methods > Text Representation
Interdisciplinary > Linguistics
Artificial Intelligence > Core AI > Language
Artificial Intelligence > Core AI > Natural Language Processing