For a professional user of MT, quality, performance and cost efficiency are critical. It is therefore surprising that only little attention – both in theory and in practice - has been given to the task of post-editing machine translated texts. This paper will focus on this important user aspect and demonstrate that substantial savings in time and effort can be achieved by implementing intelligent automatic tools. Our point of departure is the PaTrans MT-system, developed by CST and used by the Danish translation company Lingtech. An intelligent post-editing facility, Ape, has been developed and added to the system. We will outline and discuss this mechanism and its positive effects on the output. The underlying idea of the intelligent post-editing facility is to exploit the lexical and grammatical knowledge already present in the MT-system’s linguistic components. Conceptually, our approach is general, although its implementation remains system specific. Surveys of post-editor satisfaction and cost-efficiency improvements, as well as a quantitative, benchmark-based evaluation of the effect of Ape demonstrate the success of the approach and encourage further development.

This paper discusses the experiences of the specialised Danish translation company Lingtech in its use of MT for the translation of technical texts. The background and motivation for setting up Lingtech as an MT-based company is outlined. After a short general presentation of the PaTrans MT-system, the different tasks we have to perform in relation to our use of MT and the way this work is organized in order to achieve maximum cost-efficiency are described. This leads on to the discussion of problem areas for the everyday user in terms of ergonomy and tools for what may be called 'peripheral' tasks, e.g. pre- and post-editing texts, and dictionary maintenance. In the course of gaining experience in running an MT-based organization, we have identified crucial areas, where even relatively simple tools can have quite an impact on the overall productivity and profitability of using MT. Given the state-of-the-art within language technology many useful tools can now be made for the MT-user; however, we argue that too little attention has been given to these aspects so far and that they may indeed be critical to the commercial success of machine translation.