As advances in the field 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. However, these systems so far have failed to satisfy the translation community due to a fundamental misunde...

For many years MT systems and tools were used principally for the production of good-quality translations: either MT in combination with controlled (restricted) input and/or with human post-editing; or computer-based translation tools by translators. Since 1990 the situation has changed. Corporate use of MT with human assistance has continued to expand (particularly in the area of localisation)...

This paper reports on an initial study that aims to understand whether the acceptability of translation memory (TM) among translators when contrasted with machine translation (MT) unacceptability is based on users’ ability to optimise precision in match suggestions. Seven translators were asked to rate whether 60 English-German translated segments were a usable basis for a good target translati...

The usefulness of translation quality estimation (QE) to increase productivity in a computer-assisted translation (CAT) framework is a widely held assumption (Specia, 2011; Huang et al., 2014). So far, however, the validity of this assumption has not been yet demonstrated through sound evaluations in realistic settings. To this aim, we report on an evaluation involving professional translators ...

Abstract Machine translation (MT) has made significant strides and reached accuracy levels that often make the post-editing (PE) of MT output a viable alternative to manual translation. However, despite professional translators increasingly considering PE as valid stage in their workflow, little been done investigate for purpose informing training PE. Against this background, present project fo...

State-of-the-art machine translation techniques are still far from producing high quality translations. This drawback leads us to introduce an alternative approach to the translation problem that brings human expertise into the machine translation scenario. In this framework, namely Computer Assisted Translation (CAT), human translators interact with a translation system, as an assistance tool,...

Although a vast amount of contents and knowledge has been made available in electronic format and on the web in recent years, translators still do not have friendly and targeted tools at their disposal for the various aspects of a translation process, i.e., the analysis phase, automatic creation and management of the linguistic resources needed and automatic updating with the relevant informati...

Translation has historically been performed by bilinguals equipped with specialised topic knowledge. In the mid 20 century, textual theory and discourse analysis saw emphasis on a top-down, whole-text approach that paved the way for modern professional translators as linguistic transfer experts. This professionalisation was further driven by the digital revolution in the 90s which caused a huge...

Traditionally, all the translation work is done by individual translators separately. If they want to share translation expertise to the others, since all the translation knowledge and vocabulary are stored in their own computers, these can only be used by one-off user. Moreover, as the number of documents to be translated increases a lot nowadays, the translation task becomes impractical witho...

This paper describes a new methodology for developing CAT tools that assist translators of technical and scientific texts by (i) on-the-fly highlight of nominal and verbal terminology in a source language (SL) document that lifts possible syntactic ambiguity and thus essentially raises the document readability and (ii) simultaneous translation of all SL document oneand multicomponent lexical un...