Аннотация
Machine translation (MT) is a relatively new field of science. MT systems are evolving in certain directions. The article discusses the possibilities and the future of systems currently offered to public by the biggest technological companies focusing on English-Russian translation relations.Библиографические ссылки
Austermühl F. 2014. Electronic Tools for Translators, Abingdon and New York: Routledge.
Bartnicka M., Hofmann-Delbor A. 2017. Programiści i tłumacze. Wprowadzenie do lokalizacji oprogramowania, Gliwice: Helion.
Bogucki Ł. 2009. Tłumaczenie wspomagane komputerowo, Warszawa: Wydawnictwo Naukowe PWN.
Bojar O., Buck C., Federmann C., Haddow B., Koehn P., Leveling J., Monz C., Pecina P., Post M., Saint-Amand H., Soricut R., Specia L., Tamchyna A. 2014. Findings of the 2014 Workshop on Statistical Machine Translation, źródło elektroniczne: http://statmt.org/wmt14/pdf/W14-3302.pdf (dostęp: 4.11.2017).
Cronin M. 2016. Przekład w epoce cyfrowej, Kraków: Wydawnictwo Uniwersytetu Jagiellońskiego.
Ferguson N. 2016. Adaptive MT for SDL Trados Studio 2017: a self-learning machine translation engine – SDL Trados Blog, źródło elektroniczne: https://blog.sdltrados.com/adaptivemt-sdl-trados-studio-2017-transformational-mt-technology (dostęp: 30.10.2017).
Hutchins J. 2006. The first public demonstration of machine translation: the Georgetown-IBM
system, 7th January 1954, źródło elektroniczne: http://www.hutchinsweb.me.uk/GU-IBM-2005.pdf (dostęp: 30.10.2017).
Popović M. 2017. Comparing Language Related Issues for NMT and PBMT between German and English, źródło elektroniczne: https://ufal.mff.cuni.cz/pbml/108/art-popovic.pdf (dostęp: 5.11.2017).
Rehm G., Uszkoreit H. 2012. The Polish Language in the Digital Age, Berlin–Heidelberg: Springer–Verlag.
Thurmair G. 2009. Comparing different architectures of hybrid Machine Translation systems, Ontario: International Association for Machine Translation.
Wu, Y., Schuster M., Chen Z., Le Q. V., Norouzi M., Macherey W., Krikun M., Cao Y., Gao Q., Macherey K., Klingner J., Shah A., Johnson M., Liu X., Kaiser Ł., Gouws S., Kato Y. 2016. Google’s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation, źródło elektroniczne: https://arxiv.org/pdf/1609.08144.pdf (dostęp: 5.11.2017).
Yandex. Как победить морников: Яндекс запустил гибридную систему перевода – Блог Яндекса. 2017. źródło elektroniczne: https://yandex.ru/blog/company/kak-pobedit-mornikov-yandeks-zapustil-gibridnuyu-sistemu-perevoda (dostęp: 30.10.2017).
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