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Titlebook: Machine Translation; 14th China Workshop, Jiajun Chen,Jiajun Zhang Conference proceedings 2019 Springer Nature Singapore Pte Ltd. 2019 mach

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https://doi.org/10.1007/978-981-13-3083-4machine translation; artificial intelligence; computational linguistics; Natural Language Processing (N
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RST Discourse Parsing with Tree-Structured Neural Networks,hen the representations for sentences and the entire document. Experimental results show that our proposed method obtains comparable performance regarding standard discourse parsing evaluations when compared with state-of-the-art systems.
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A Grammatical Analysis on Machine Translation Errors,nces between English and Chinese. The effects of these differences on machine translation are also analyzed, while future improvement suggestions on machine translation technology are provided accordingly.
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Neural Name Translation Improves Neural Machine Translation,ranslation model is further used to derive high quality NE alignment in the bilingual training corpus. With the integration of NE translation and alignment modules, our NMT system is able to surpass the baseline system by 2.9 BLEU points on the Chinese to English task.
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