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Pregled bibliografske jedinice broj: 913277

Dealing with Data Sparseness in SMT with Factored Models and Morphological Expansion: a Case Study on Croatian


Sanchez-Cartagena, Victor M.; Ljubešić, Nikola; Klubička, Filip
Dealing with Data Sparseness in SMT with Factored Models and Morphological Expansion: a Case Study on Croatian // Baltic Journal of Modern Computing, 4 (2016), 2; 354-360 (međunarodna recenzija, članak, znanstveni)


Naslov
Dealing with Data Sparseness in SMT with Factored Models and Morphological Expansion: a Case Study on Croatian

Autori
Sanchez-Cartagena, Victor M. ; Ljubešić, Nikola ; Klubička, Filip

Izvornik
Baltic Journal of Modern Computing (2255-8942) 4 (2016), 2; 354-360

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Data sparseness, factored translation models, morphological expansion

Sažetak
This paper describes our experience using available linguistic resources for Croatian in order to address data sparseness when building an English-to-Croatian general domain phrase- based statistical machine translation system. We report the results obtained with factored translation models and morphological expansion, highlight the impact of the algorithm used for tagging the corpora, and show that the improvement brought by these methods is compatible with the application of data selection on out-of-domain parallel corpora.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti



POVEZANOST RADA


Ustanove
Filozofski fakultet, Zagreb

Autor s matičnim brojem:
Nikola Ljubešić, (272820)

Časopis indeksira:


  • Web of Science Core Collection (WoSCC)
    • Emerging Sources Citation Index (ESCI)