期刊名称：The Prague Bulletin of Mathematical Linguistics
印刷版ISSN：0032-6585
电子版ISSN：1804-0462
出版年度：2017
卷号：108
期号：1
页码：209-220
DOI：10.1515/pralin-2017-0021
语种：English
出版社：Walter de Gruyter GmbH
摘要：This work presents an extensive comparison of language related problems for neural machine translation and phrase-based machine translation between German and English. The explored issues are related both to the language characteristics as well as to the machine translation process and, although related, are going beyond typical translation error classes. It is shown that the main advantage of the NMT system consists of better handling of verbs, English noun collocations, German compound words, phrase structure as well as articles. In addition, it is shown that the main obstacles for the NMT system are prepositions, translation of English (source) ambiguous words and generating English (target) continuous tenses. Although in total there are less issues for the NMT system than for the PBMT system, many of them are complementary – only about one third of the sentences deals with the same issues, and for about 40% of the sentences the issues are completely different. This means that combination/hybridisation of the NMT and PBMT approaches is a promising direction for improving both types of systems.
