Bootstrapping a Hybrid MT System to a New Language Pair
João António Rodrigues, Nuno Rendeiro, Andreia Querido, Sanja Štajner, António Branco
Abstract
The usual concern when opting for a rule-based or a hybrid machine translation (MT) system is how much effort is required to adapt the system to a different language pair or a new domain. In this paper, we describe a way of adapting an existing hybrid MT system to a new language pair, and show that such a system can outperform a standard phrase-based statistical machine translation system with an average of 10 persons/month of work. This is specifically important in the case of domain-specific MT for which there is not enough parallel data for training a statistical machine translation system.- Anthology ID:
- L16-1438
- 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:
- 2762–2765
- Language:
- URL:
- https://aclanthology.org/L16-1438
- DOI:
- Cite (ACL):
- João António Rodrigues, Nuno Rendeiro, Andreia Querido, Sanja Štajner, and António Branco. 2016. Bootstrapping a Hybrid MT System to a New Language Pair. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 2762–2765, Portorož, Slovenia. European Language Resources Association (ELRA).
- Cite (Informal):
- Bootstrapping a Hybrid MT System to a New Language Pair (Rodrigues et al., LREC 2016)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/L16-1438.pdf