2022
EMNLP
EMNLP 2022
Parallel Corpus Filtering for Japanese Text Simplification
Abstract
AbstractWe propose a method of parallel corpus filtering for Japanese text simplification. The parallel corpus for this task contains some redundant wording. In this study, we first identify the type and size of noisy sentence pairs in the Japanese text simplification corpus. We then propose a method of parallel corpus filtering to remove each type of noisy sentence pair. Experimental results show that filtering the training parallel corpus with the proposed method improves simplification performance.
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Interdisciplinary Bridge
— Artificial Intelligence and Machine Learning and Natural Language Processing
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Keyword Pioneer
— noisy sentence pair
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning