Abstract
In this paper we describe a rule-based, bi-directional machine translation system for the Finnish—English language pair. The baseline system was based on the existing data of FinnWordNet, omorfi and apertium-eng. We have built the disambiguation, lexical selection and translation rules by hand. The dictionaries and rules have been developed based on the shared task data. We describe in this article the use of the shared task data as a kind of a test-driven development workflow in RBMT development and show that it suits perfectly to a modern software engineering continuous integration workflow of RBMT and yields big increases to BLEU scores with minimal effort.- Anthology ID:
- W19-5336
- Volume:
- Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 335–341
- Language:
- URL:
- https://aclanthology.org/W19-5336
- DOI:
- 10.18653/v1/W19-5336
- Cite (ACL):
- Tommi Pirinen. 2019. Apertium-fin-eng–Rule-based Shallow Machine Translation for WMT 2019 Shared Task. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 335–341, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Apertium-fin-eng–Rule-based Shallow Machine Translation for WMT 2019 Shared Task (Pirinen, WMT 2019)
- PDF:
- https://preview.aclanthology.org/nodalida-main-page/W19-5336.pdf