2017
ACL
ACL 2017
One-Shot Neural Cross-Lingual Transfer for Paradigm Completion
Abstract
AbstractWe present a novel cross-lingual transfer method for paradigm completion, the task of mapping a lemma to its inflected forms, using a neural encoder-decoder model, the state of the art for the monolingual task. We use labeled data from a high-resource language to increase performance on a low-resource language. In experiments on 21 language pairs from four different language families, we obtain up to 58% higher accuracy than without transfer and show that even zero-shot and one-shot learning are possible. We further find that the degree of language relatedness strongly influences the ability to transfer morphological knowledge.
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Interdisciplinary Bridge
— Artificial Intelligence and Machine Learning and Natural Language Processing
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Trend Setter
— Few-Shot Learning
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Keyword Pioneer
— paradigm completion
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Hot Topic Early Bird
— cross-lingual transfer
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Cross-Pollinator
— Artificial Intelligence, Computer Vision, Deep Learning, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Natural Language Processing, Robotics, Speech & Audio
Authors
Topics
Artificial Intelligence > Learning Paradigms > Few-Shot Learning
Natural Language Processing > Resources & Methods > Multilingual NLP
Interdisciplinary > Linguistics > Computational Linguistics
Machine Learning > Learning Paradigms > Few-Shot Learning
Machine Learning > Learning Types > Transfer Learning
Natural Language Processing > Resources & Methods > Transfer Learning