Abstract
Reordering is one source of error in statistical machine translation (SMT). This paper extends the study of the statistical machine reordering (SMR) approach, which uses the powerful techniques of the SMT systems to solve reordering problems. Here, the novelties yield in: (1) using the SMR approach in a SMT phrase-based system, (2) adding a feature function in the SMR step, and (3) analyzing the reordering hypotheses at several stages. Coherent improvements are reported in the TC-STAR task (Es/En) at a relatively low computational cost.- Anthology ID:
- 2008.amta-papers.6
- Volume:
- Proceedings of the 8th Conference of the Association for Machine Translation in the Americas: Research Papers
- Month:
- October 21-25
- Year:
- 2008
- Address:
- Waikiki, USA
- Venue:
- AMTA
- SIG:
- Publisher:
- Association for Machine Translation in the Americas
- Note:
- Pages:
- 82–88
- Language:
- URL:
- https://aclanthology.org/2008.amta-papers.6
- DOI:
- Cite (ACL):
- Marta R. Costa-Jussà and José A. R. Fonollosa. 2008. Computing multiple weighted reordering hypotheses for a phrase-based statistical machine translation system. In Proceedings of the 8th Conference of the Association for Machine Translation in the Americas: Research Papers, pages 82–88, Waikiki, USA. Association for Machine Translation in the Americas.
- Cite (Informal):
- Computing multiple weighted reordering hypotheses for a phrase-based statistical machine translation system (Costa-Jussà & Fonollosa, AMTA 2008)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2008.amta-papers.6.pdf