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master's thesis
Comparative Analysis of MemoQ Adaptive Generative Translation (AGT) with Conventional Machine Translation (MT) Engines
Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Humanities and Social Sciences, 2024. urn:nbn:hr:142:380153
Aladrović, Josip
Josip Juraj Strossmayer University of Osijek
Faculty of Humanities and Social Sciences
Department of English Language and Literature

Institutional repository: FFOS-repository

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Aladrović, J. (2024). Comparative Analysis of MemoQ Adaptive Generative Translation (AGT) with Conventional Machine Translation (MT) Engines (Master's thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Humanities and Social Sciences. Retrieved from https://urn.nsk.hr/urn:nbn:hr:142:380153

Aladrović, Josip. "Comparative Analysis of MemoQ Adaptive Generative Translation (AGT) with Conventional Machine Translation (MT) Engines." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Humanities and Social Sciences, 2024. https://urn.nsk.hr/urn:nbn:hr:142:380153

Aladrović, Josip. "Comparative Analysis of MemoQ Adaptive Generative Translation (AGT) with Conventional Machine Translation (MT) Engines." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Humanities and Social Sciences, 2024. https://urn.nsk.hr/urn:nbn:hr:142:380153

Aladrović, J. (2024). 'Comparative Analysis of MemoQ Adaptive Generative Translation (AGT) with Conventional Machine Translation (MT) Engines', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Humanities and Social Sciences, accessed 13 January 2025, https://urn.nsk.hr/urn:nbn:hr:142:380153

Aladrović J. Comparative Analysis of MemoQ Adaptive Generative Translation (AGT) with Conventional Machine Translation (MT) Engines [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Humanities and Social Sciences; 2024 [cited 2025 January 13] Available at: https://urn.nsk.hr/urn:nbn:hr:142:380153

J. Aladrović, "Comparative Analysis of MemoQ Adaptive Generative Translation (AGT) with Conventional Machine Translation (MT) Engines", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Humanities and Social Sciences, Osijek, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:142:380153

Metadata
TitleComparative Analysis of MemoQ Adaptive Generative Translation (AGT) with Conventional Machine Translation (MT) Engines
Title (croatian)Usporedna analiza adaptivnog generativnog prijevoda (AGT) s konvencionalnim strojnim prijevodom (MT)
AuthorJosip Aladrović
MentorMarija Omazić (mentor)
Committee memberDubravka Vidaković Erdeljić (predsjednik povjerenstva)
Committee memberMarija Omazić (član povjerenstva)
Committee memberGoran Schmidt (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Humanities and Social Sciences
(Department of English Language and Literature)
Osijek
Defense date and country2024-09-30, Croatia
Scientific / art field,
discipline and subdiscipline		HUMANISTIC SCIENCES
Philology
Anglistics
Abstract
This thesis aims to conduct a comprehensive comparative analysis between memoQ Adaptive Generative Translation (AGT) and conventional Machine Translation (MT) engines regarding their efficacy and accuracy in translating English language texts into Croatian. The study will investigate various aspects such as translation accuracy, fluency, and terminological consistency by the means qualitative analyses and of automatic evaluation provided by the MATEO evaluation platform and selected metrics (BLEU, ChrF, and COMET). Additionally, it will explore potential drawbacks associated with each translation approach. By employing empirical research methods and a case study, this thesis seeks to provide insights into the strengths and limitations of memoQ AGT compared to standard MT engines in meeting translation requirements in the English-Croatian language pair. The findings of this research are expected to contribute to the ongoing discourse on the advancements in machine translation technology.
Abstract (croatian)
Cilj je ovog rada sveobuhvatna usporedna analiza alata memoQ Adaptive Generative Translation (AGT) s ostalim konvencionalnim alatima za strojno prevođenje, s obzirom na učinkovitost i točnost prijevoda teksta s engleskog jezika na hrvatski jezik. Rad će istražiti razne aspekte poput točnosti prijevoda, tečnosti i terminološke dosljednosti u vidu kvalitativne analize i automatske procjene koju pruža platforma MATEO odabranim metrikama (BLEU, ChrF i COMET). Rad će također istražiti moguće nedostatke s obzirom na pojedini pristup prijevodu. Provedbom metoda empirijskog istraživanja i studije slučaja, ovaj rad cilja dati uvid u prednosti i ograničenja memoQ AGT-a u usporedbi sa standardnim alatima za strojno prevođenje s obzirom na zadovoljavanje kriterija prijevoda u jezičnoj kombinaciji engleski-hrvatski. Očekuje se da će rezultati ovog istraživanja doprinijeti tekućoj raspravi o napretku tehnologija strojnog prevođenja.
Keywords
Keywords (croatian)
Languageenglish
URN:NBNurn:nbn:hr:142:380153
Study programmeTitle: English Language and Literature (double major); specializations in: Teacher Education, Philology, Translation Studies
Course: Translation Studies
Study programme type: university
Study level: graduate
Academic / professional title: sveučilišni/a magistar/magistra engleskog jezika i književnosti / sveučilišni/a magistar/magistra edukacije engleskog jezika i književnosti (sveučilišni/a magistar/magistra engleskog jezika i književnosti / sveučilišni/a magistar/magistra edukacije engleskog jezika i književnosti)
Study programmeTitle: Croatian Language and Literature (double major); specializations in: Teacher Education, Research Studies
Course: Teacher Education
Study programme type: university
Study level: graduate
Academic / professional title: sveučilišni/a magistar/magistra edukacije hrvatskog jezika i književnosti / sveučilišni/a magistar/magistra hrvatskog jezika i književnosti (sveučilišni/a magistar/magistra edukacije hrvatskog jezika i književnosti / sveučilišni/a magistar/magistra hrvatskog jezika i književnosti)
Type of resourceText
File originBorn digital
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Created on2024-11-28 18:24:17