Multi-Engine Machine Translation by Recursive Sentence Decomposition
Bart Mellebeek, Karolina Owczarzak, Josef Van Genabith, Andy Way
Abstract
In this paper, we present a novel approach to combine the outputs of multiple MT engines into a consensus translation. In contrast to previous Multi-Engine Machine Translation (MEMT) techniques, we do not rely on word alignments of output hypotheses, but prepare the input sentence for multi-engine processing. We do this by using a recursive decomposition algorithm that produces simple chunks as input to the MT engines. A consensus translation is produced by combining the best chunk translations, selected through majority voting, a trigram language model score and a confidence score assigned to each MT engine. We report statistically significant relative improvements of up to 9% BLEU score in experiments (English→Spanish) carried out on an 800-sentence test set extracted from the Penn-II Treebank.- Anthology ID:
- 2006.amta-papers.13
- 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:
- 110–118
- Language:
- URL:
- https://aclanthology.org/2006.amta-papers.13
- DOI:
- Cite (ACL):
- Bart Mellebeek, Karolina Owczarzak, Josef Van Genabith, and Andy Way. 2006. Multi-Engine Machine Translation by Recursive Sentence Decomposition. In Proceedings of the 7th Conference of the Association for Machine Translation in the Americas: Technical Papers, pages 110–118, Cambridge, Massachusetts, USA. Association for Machine Translation in the Americas.
- Cite (Informal):
- Multi-Engine Machine Translation by Recursive Sentence Decomposition (Mellebeek et al., AMTA 2006)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2006.amta-papers.13.pdf