Abstract
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.
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Danielsson, P., Mühlenbock, K. (2000). Small but Efficient: The Misconception of High- Frequency Words in Scandinavian Translation. In: White, J.S. (eds) Envisioning Machine Translation in the Information Future. AMTA 2000. Lecture Notes in Computer Science(), vol 1934. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39965-8_16
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DOI: https://doi.org/10.1007/3-540-39965-8_16
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