Improving Online Machine Translation Systems
Bart Mellebeek, Anna Khasin, Karolina Owczarzak, Josef Van Genabith, Andy Way
Abstract
In (Mellebeek et al., 2005), we proposed the design, implementation and evaluation of a novel and modular approach to boost the translation performance of existing, wide-coverage, freely available machine translation systems, based on reliable and fast automatic decomposition of the translation input and corresponding composition of translation output. Despite showing some initial promise, our method did not improve on the baseline Logomedia1 and Systran2 MT systems. In this paper, we improve on the algorithm presented in (Mellebeek et al., 2005), and on the same test data, show increased scores for a range of automatic evaluation metrics. Our algorithm now outperforms Logomedia, obtains similar results to SDL3 and falls tantalisingly short of the performance achieved by Systran.- Anthology ID:
- 2005.mtsummit-papers.38
- Volume:
- Proceedings of Machine Translation Summit X: Papers
- Month:
- September 13-15
- Year:
- 2005
- Address:
- Phuket, Thailand
- Venue:
- MTSummit
- SIG:
- Publisher:
- Note:
- Pages:
- 290–297
- Language:
- URL:
- https://aclanthology.org/2005.mtsummit-papers.38
- DOI:
- Cite (ACL):
- Bart Mellebeek, Anna Khasin, Karolina Owczarzak, Josef Van Genabith, and Andy Way. 2005. Improving Online Machine Translation Systems. In Proceedings of Machine Translation Summit X: Papers, pages 290–297, Phuket, Thailand.
- Cite (Informal):
- Improving Online Machine Translation Systems (Mellebeek et al., MTSummit 2005)
- PDF:
- https://preview.aclanthology.org/nodalida-main-page/2005.mtsummit-papers.38.pdf