Abstract
Machine translation (MT) is - not only historically - a prime application of language technology. After years of seeming stagnation, the price pressure on language service providers (LSPs) and the increased translation need have led to new momentum for the inclusion of MT in industrial translation workflows. On the research side, this trend is backed by improvements in translation performance, especially in the area of hybrid MT approaches. Nevertheless, it is clear that translation quality is far from perfect in many applications. Therefore, human post-editing today seems the only way to go. This chapter reports on a system that is being developed as part of taraXŰ, an ongoing joint project between industry and research partners. By combining state-of-the-art language technology applications, developing informed selection mechanisms using the outputs of different MT engines, and incorporating qualified translator feedback throughout the development process, the project aims to make MT economically feasible and technically usable.
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Burchardt, A., Tscherwinka, C., Avramidis, E., Uszkoreit, H. (2013). Machine Translation at Work. In: Przepiórkowski, A., Piasecki, M., Jassem, K., Fuglewicz, P. (eds) Computational Linguistics. Studies in Computational Intelligence, vol 458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34399-5_13
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