2019
EMNLP
EMNLP 2019
Synchronously Generating Two Languages with Interactive Decoding
Abstract
AbstractIn this paper, we introduce a novel interactive approach to translate a source language into two different languages simultaneously and interactively. Specifically, the generation of one language relies on not only previously generated outputs by itself, but also the outputs predicted in the other language. Experimental results on IWSLT and WMT datasets demonstrate that our method can obtain significant improvements over both conventional Neural Machine Translation (NMT) model and multilingual NMT model.
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Interdisciplinary Bridge
— Deep Learning and Machine Learning and Natural Language Processing
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Keyword Pioneer
— interactive decoding
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Hot Topic Early Bird
— simultaneous translation
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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