Demo of iMAG Possibilities: MT-postediting, Translation Quality Evaluation, Parallel Corpus Production

iMAG : MT-postediting, translation quality evaluation and parallel corpus production (iMAG : post-édition, évaluation de qualité de TA et production d'un corpus parallèle) [in French]

Online production of HQ parallel corpora and permanent task-based evaluation of multiple MT systems: both can be obtained through iMAGs with no added cost

An interactive Multilingual Access Gateway (iMAG) dedicated to a website S (iMAG-S) is a good tool to make S accessible in many languages immediately and without editorial responsibility. Visitors of S as well as paid or unpaid posteditors and moderators contribute to the continuous and incremental improvement of the most important textual segments, and eventually of all. In this approach, pre-...

The taraXÜ corpus of human-annotated machine translations

Human translators are the key to evaluating machine translation (MT) quality and also to addressing the so far unanswered question when and how to use MT in professional translation workflows. This paper describes the corpus developed as a result of a detailed large scale human evaluation consisting of three tightly connected tasks: ranking, error classification and post-editing.

A Web Service Enabling Gradable Post-edition of Pre-translations Pro- duced by Existing Translation Tools: Practical Use to Provide High- quality Translation of an Online Encyclopedia

SECTra_w is a Web-based system offering several services, such as supporting MT evaluation campaigns and online post-editing of MT results, to produce reference translations adapted to classical MT systems not built by machine learning from a parallel corpus. The service we are interested in here is the possibility for its users to import a document, or a set of documents (not only a list of pr...

Multi-Engine and Multi-Alignment Based Automatic Post-Editing and its Impact on Translation Productivity

In this paper we combine two strands of machine translation (MT) research: automatic postediting (APE) and multi-engine (system combination) MT. APE systems learn a target-languageside second stage MT system from the data produced by human corrected output of a first stage MT system, to improve the output of the first stage MT in what is essentially a sequential MT system combination architectu...