Language Related Issues for Machine Translation between Closely Related South Slavic Languages

نویسندگان

  • Maja Popovic
  • Mihael Arcan
  • Filip Klubicka
چکیده

Machine translation between closely related languages is less challenging and exhibits a smaller number of translation errors than translation between distant languages, but there are still obstacles which should be addressed in order to improve such systems. This work explores the obstacles for machine translation systems between closely related South Slavic languages, namely Croatian, Serbian and Slovenian. Statistical systems for all language pairs and translation directions are trained using parallel texts from different domains, however mainly on spoken language i.e. subtitles. For translation between Serbian and Croatian, a rule-based system is also explored. It is shown that for all language pairs and for both translation systems, the main obstacles are the differences between syntactic properties.

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تاریخ انتشار 2016