prikaz prve stranice dokumenta Errors in Machine Translation from Croatian to English: a Corpus-based Approach
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master's thesis
Errors in Machine Translation from Croatian to English: a Corpus-based Approach
2020. urn:nbn:hr:186:395434
Zagorec, Dario
University of Rijeka
Faculty of Humanities and Social Sciences
Department of English Language and Literature

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Zagorec, D. (2020). Errors in Machine Translation from Croatian to English: a Corpus-based Approach (Master's thesis). Rijeka: University of Rijeka, Faculty of Humanities and Social Sciences. Retrieved from https://urn.nsk.hr/urn:nbn:hr:186:395434

Zagorec, Dario. "Errors in Machine Translation from Croatian to English: a Corpus-based Approach." Master's thesis, University of Rijeka, Faculty of Humanities and Social Sciences, 2020. https://urn.nsk.hr/urn:nbn:hr:186:395434

Zagorec, Dario. "Errors in Machine Translation from Croatian to English: a Corpus-based Approach." Master's thesis, University of Rijeka, Faculty of Humanities and Social Sciences, 2020. https://urn.nsk.hr/urn:nbn:hr:186:395434

Zagorec, D. (2020). 'Errors in Machine Translation from Croatian to English: a Corpus-based Approach', Master's thesis, University of Rijeka, Faculty of Humanities and Social Sciences, accessed 10 July 2024, https://urn.nsk.hr/urn:nbn:hr:186:395434

Zagorec D. Errors in Machine Translation from Croatian to English: a Corpus-based Approach [Master's thesis]. Rijeka: University of Rijeka, Faculty of Humanities and Social Sciences; 2020 [cited 2024 July 10] Available at: https://urn.nsk.hr/urn:nbn:hr:186:395434

D. Zagorec, "Errors in Machine Translation from Croatian to English: a Corpus-based Approach", Master's thesis, University of Rijeka, Faculty of Humanities and Social Sciences, Rijeka, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:186:395434

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Metadata
TitleErrors in Machine Translation from Croatian to English: a Corpus-based Approach
AuthorDario Zagorec
MentorMirjana Borucinsky (mentor)
Committee memberMarija Brala-Vukanović (predsjednik povjerenstva)
Committee memberMirjana Borucinsky (član povjerenstva)
Committee memberAnita Memišević (član povjerenstva)
GranterUniversity of Rijeka
Faculty of Humanities and Social Sciences
(Department of English Language and Literature)
Rijeka
Defense date and country2020-09-14, Croatia
Scientific / art field,
discipline and subdiscipline		HUMANISTIC SCIENCES
Philology
Scientific / art field,
discipline and subdiscipline		SOCIAL SCIENCES
Pedagogy
Abstract
A once heavily flawed method of translation, machine translation has improved and continues to improve every day. However, with the plethora of errors that machine translation systems make, machine translation is undeniably inferior to human translation. This paper analyzes a corpus of texts translated by Google Translate for different types of errors. The results show that Google Translate committed an abundance of lexical, morphosyntactic and stylistic errors, highlighting the limitations of machine translation at this time.
Keywords
Languageenglish
URN:NBNurn:nbn:hr:186:395434
Study programmeTitle: English Language and Literature (double major); specializations in: Teaching Track
Course: Teaching Track
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra edukacije engleskog jezika i književnosti (magistar/magistra edukacije engleskog jezika i književnosti)
Study programmeTitle: Pedagogy (double major)
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra pedagogije (magistar/magistra pedagogije)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2021-02-01 11:28:12