Abstract
This paper presents a novel system for sub-sentential alignment of bilingual sentence pairs, however few, using readily-available machine-readable bilingual dictionaries. Performance is evaluated against an existing gold-standard parallel corpus where word alignments are annotated, showing results that are a considerable improvement on a comparable system and on GIZA++ performance for the same corpus. Since naïve application of the system for N languages would require N(N - 1) dictionaries, it is also evaluated using a pivot language, where only 2(N - 1) dictionaries would be required, with surprisingly similar performance. The system is proposed as an alternative to statistical methods, for use with very small corpora or for ‘on-the-fly’ alignment.- Anthology ID:
- 2014.amta-researchers.7
- Volume:
- Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track
- Month:
- October 22-26
- Year:
- 2014
- Address:
- Vancouver, Canada
- Venue:
- AMTA
- SIG:
- Publisher:
- Association for Machine Translation in the Americas
- Note:
- Pages:
- 83–95
- Language:
- URL:
- https://aclanthology.org/2014.amta-researchers.7
- DOI:
- Cite (ACL):
- Kevin Flanagan. 2014. Bilingual phrase-to-phrase alignment for arbitrarily-small datasets. In Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track, pages 83–95, Vancouver, Canada. Association for Machine Translation in the Americas.
- Cite (Informal):
- Bilingual phrase-to-phrase alignment for arbitrarily-small datasets (Flanagan, AMTA 2014)
- PDF:
- https://preview.aclanthology.org/paclic-22-ingestion/2014.amta-researchers.7.pdf