Pregled bibliografske jedinice broj: 1117718
Machine translation system for the industry domain and Croatian language
Machine translation system for the industry domain and Croatian language // Journal of information and organizational sciences, 44 (2020), 1; 33-50 doi:10.31341/jios.44.1.2 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1117718 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Machine translation system for the industry domain and Croatian language
Autori
Dunđer, Ivan
Izvornik
Journal of information and organizational sciences (1846-3312) 44
(2020), 1;
33-50
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
statistical machine translation ; domain adaptation ; automatic quality metrics ; human quality evaluation ; error classification ; Croatian language ; information and communication sciences
Sažetak
Machine translation is increasingly becoming a hot research topic in information and communication sciences, computer science and computational linguistics, due to the fact that it enables communication and transferring of meaning across different languages. As the Croatian language can be considered low-resourced in terms of available services and technology, development of new domain-specific machine translation systems is important, especially due to raised interest and needs of industry, academia and everyday users. Machine translation is not perfect, but it is crucial to assure acceptable quality, which is purpose-dependent. In this research, different statistical machine translation systems were built – but one system utilized domain adaptation in particular, with the intention of boosting the output of machine translation. Afterwards, extensive evaluation has been performed – in form of applying several automatic quality metrics and human evaluation with focus on various aspects. Evaluation is done in order to assess the quality of specific machine-translated text.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti
POVEZANOST RADA
Projekti:
NadSve-Sveučilište u Zagrebu-43-922-1011 - Disruptivne tehnologije u stvaranju novoga znanja: strojno učenje i podatkovna analitika s modelima primjene u specijaliziranim domenama (Seljan, Sanja, NadSve - Natječaj za dodjelu sredstava za financiranje temeljne znanstvene djelatnosti u 2019. godini dodijeljenih Filozofskom fakultetu Sveučilištu u Zagrebu) ( CroRIS)
Ustanove:
Filozofski fakultet, Zagreb
Profili:
Ivan Dunđer
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Emerging Sources Citation Index (ESCI)
- Scopus