Abstract
This paper presents how an state-of-the-art SMT system is enriched by using an extra in-domain parallel corpora extracted from Wikipedia. We collect corpora from parallel titles and from parallel fragments in comparable articles from Wikipedia. We carried out an evaluation with a double objective: evaluating the quality of the extracted data and evaluating the improvement due to the domain-adaptation. We think this can be very useful for languages with limited amount of parallel corpora, where in-domain data is crucial to improve the performance of MT sytems. The experiments on the Spanish-English language pair improve a baseline trained with the Europarl corpus in more than 2 points of BLEU when translating in the Computer Science domain.- Anthology ID:
- L16-1351
- 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:
- 2209–2213
- Language:
- URL:
- https://aclanthology.org/L16-1351
- DOI:
- Cite (ACL):
- Gorka Labaka, Iñaki Alegria, and Kepa Sarasola. 2016. Domain Adaptation in MT Using Titles in Wikipedia as a Parallel Corpus: Resources and Evaluation. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 2209–2213, Portorož, Slovenia. European Language Resources Association (ELRA).
- Cite (Informal):
- Domain Adaptation in MT Using Titles in Wikipedia as a Parallel Corpus: Resources and Evaluation (Labaka et al., LREC 2016)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/L16-1351.pdf