Abstract
State-of-the-art statistical machine translation is based on alignments between phrases – sequences of words in the source and target sentences. The learning step in these systems often relies on alignments between words. It is often assumed that the quality of this word alignment is critical for translation. However, recent results suggest that the relationship between alignment quality and translation quality is weaker than previously thought. We investigate this question directly, comparing the impact of high-quality alignments with a carefully constructed set of degraded alignments. In order to tease apart various interactions, we report experiments investigating the impact of alignments on different aspects of the system. Our results confirm a weak correlation, but they also illustrate that more data and better feature engineering may be more beneficial than better alignment.- Anthology ID:
- 2006.amta-papers.11
- Volume:
- Proceedings of the 7th Conference of the Association for Machine Translation in the Americas: Technical Papers
- Month:
- August 8-12
- Year:
- 2006
- Address:
- Cambridge, Massachusetts, USA
- Venue:
- AMTA
- SIG:
- Publisher:
- Association for Machine Translation in the Americas
- Note:
- Pages:
- 90–99
- Language:
- URL:
- https://aclanthology.org/2006.amta-papers.11
- DOI:
- Cite (ACL):
- Adam Lopez and Philip Resnik. 2006. Word-Based Alignment, Phrase-Based Translation: What’s the Link?. In Proceedings of the 7th Conference of the Association for Machine Translation in the Americas: Technical Papers, pages 90–99, Cambridge, Massachusetts, USA. Association for Machine Translation in the Americas.
- Cite (Informal):
- Word-Based Alignment, Phrase-Based Translation: What’s the Link? (Lopez & Resnik, AMTA 2006)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2006.amta-papers.11.pdf