As advances in the eld of machine translation (MT) continue to allow for greater
\ndistribution of multi-lingual information, an increasing number of browser-based
\ntoolkits are being developed in an attempt to empower translators, and decrease
\nthe gap between speed, and quality of output. However, these systems so far have
\nfailed to satisfy the translation community due to a fundamental misunderstanding
\nof the way translators work. There has been an essential divergence in the study
\nand implementation of machine translation systems|away from the original goal
\nof providing perfect target-language texts, towards an attempt to provide output
\nthat can be largely understood for quick dissemination. The realisation that current
\nmethodology in the eld does not allow for such high quality to be attained has
\nturned researchers’ attentions to the development of systems that act as supporting
\nprocesses during several of the traditional stages of translation. Nonetheless, such
\ne orts have continued on the assumption that high quality translation from the get-
\ngo is the most important factor, rather than assessing how translators’ work
\nows
\nreact to poor quality target language text generated by such systems. Our aim has
\nbeen to identify techniques that reduce the time that translators spend on the whole
\ntransfer process – by realising that a SMT core can provide much more than a raw
\ntranslation, even at this relatively early stage in its development.
\nOur research evaluates the shortcomings of existing systems, and proposes a new
\nkind of integrated online toolkit that addresses these limitations based on an under-
\nstanding of the most signi cant and unnecessary struggles between translators and
\nMT systems. Consequently we believe that with just a handful of changes it is pos-
\nsible to envisage an arrangement that will allow translators to regularly outperform
\nnon-MT-based working strategies, both in terms of speed and quality.<\/p>\n","protected":false},"excerpt":{"rendered":"
As advances in the eld of machine translation (MT) continue to allow for greater distribution of multi-lingual information, an increasing number of browser-based toolkits are being developed in an attempt to empower translators, and decrease the gap between speed, and quality of output. 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