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Small but efficient: the misconception of high-frequency words in Scandinavian translation

机译:小但高效:斯堪的纳维亚翻译中的高频词误解

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Machine translation has proved itself to be easier between languages that are closely related, such as German and English, while far apart languages, such as Chinese and English, encounter much more problems. The present study focuses upon Swedish and Norwegian; two languages so closely related that they would be referred to as dialects if it were not for the fact that they had a Royal house and an army connected to each of them. Despite their similarity though, some differences make the translation phase much less straight-forward than what could be expected. Taking the outset in sentence aligned parallel texts, this study aims at highlighting some of the differences, and to formalise the results. In order to do so, the texts have been aligned on smaller units, by a simple cognate alignment method. Not at all surprising, the longer words were easier to align, while shorter and often high-frequent words became a problem. Also when trying to align to a specific word sense in a dictionary, content words rendered better results. Therefore, we abandoned the use of single-word units, and searched for multi-word units whenever possible. This study reinforces the view that Machine Translation should rest upon methods based on multiword unit searches.
机译:机器翻译已证明自己在密切相关的语言中更容易,例如德语和英语,而汉英和英文等语言则遇到更多问题。本研究重点介绍瑞典和挪威语;两种语言如此密切相关,因为如果它没有皇家房子和陆军连接到他们每个人的事实,他们将被称为方言。尽管他们的相似之处,但一些差异使翻译阶段不如预期的那么直接。在句子中取得一开始并行的并行文本,本研究旨在突出一些差异,并将结果正式化。为此,通过简单的同源对准方法,文本已经在较小的单元上对齐。根本不令人惊讶,越来越越来越容易对齐,而较短且经常高频繁的单词变成了问题。此外,当尝试将字典中的特定字感对齐时,内容单词呈现更好的结果。因此,我们放弃了单词单元的使用,并尽可能在多字单元中搜索。本研究强化了基于多字单元搜索的机器翻译应搁置的视图。

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