Collecting Language Resources for the Latvian e-Government Machine Translation Platform

Roberts Rozis, Andrejs Vasiļjevs, Raivis Skadiņš


Abstract
This paper describes corpora collection activity for building large machine translation systems for Latvian e-Government platform. We describe requirements for corpora, selection and assessment of data sources, collection of the public corpora and creation of new corpora from miscellaneous sources. Methodology, tools and assessment methods are also presented along with the results achieved, challenges faced and conclusions made. Several approaches to address the data scarceness are discussed. We summarize the volume of obtained corpora and provide quality metrics of MT systems trained on this data. Resulting MT systems for English-Latvian, Latvian English and Latvian Russian are integrated in the Latvian e-service portal and are freely available on website HUGO.LV. This paper can serve as a guidance for similar activities initiated in other countries, particularly in the context of European Language Resource Coordination action.
Anthology ID:
L16-1202
Volume:
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:
May
Year:
2016
Address:
Portorož, Slovenia
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
1270–1276
Language:
URL:
https://aclanthology.org/L16-1202
DOI:
Bibkey:
Cite (ACL):
Roberts Rozis, Andrejs Vasiļjevs, and Raivis Skadiņš. 2016. Collecting Language Resources for the Latvian e-Government Machine Translation Platform. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 1270–1276, Portorož, Slovenia. European Language Resources Association (ELRA).
Cite (Informal):
Collecting Language Resources for the Latvian e-Government Machine Translation Platform (Rozis et al., LREC 2016)
Copy Citation:
PDF:
https://aclanthology.org/L16-1202.pdf