Improving online machine translation systems
Bart Mellebeek, Anna Khasin, Karolina Owczarzak, Josef van Genabith, Andy Way · Dublin City University Open Access Institutional Repository (Dublin City University) · 2005
In (Mellebeek et al., 2005), we proposed the de-sign, 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 com-position of translation output. Despite showing some initial promise, our method did not im-prove on the baseline Logomedia1 and Systran2 MT systems. In this paper, we improve on the algorithm pre-sented 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 re-sults to SDL3 and falls tantalisingly short of the performance achieved by Systran. 1