Language Technologies

 

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Please note that the project factsheets will no longer be updated.  All information relevant to the project can be found on the CORDIS factsheet .  This is updated on a regular basis with public deliverables, etc.

CASMACAT - Cognitive Analysis and Statistical Methods for Advanced Computer Aided Translation

287576 - STREP

casmacat-logo.jpg

At a glance

FP7-ICT-2011-7 - Language technologies

European integration and globalisation beyond it increases cross-border commercial, cultural, and political interaction. However, while the significance of political borders diminishes, the risk remains that the world will stays fractured by linguistic boundaries. The need to address each individual in a language that she speaks, and ideally in her native language, requires a huge amount of translation work.

Challenge

While there have been significant improvements to machine translation technology, the vast majority of this work is targeted towards bulk translation that is good enough or fit for use . A user on the Internet is satisfied with a rough translation, if it fills her information need. Opposed to that is the demand for high quality translations by the marketplace: the translation of reports and announcements of multi-national organizations, marketing material and product descriptions of commercial companies, and many other localization needs. Such high quality translations are still almost exclusively provided by human translators.

Productivity of human translators can be increased with computer aided translation (CAT) tools: translation memories are standard in the translation industry, but post-editing machine translation output is only slowly becoming an increasingly used practice. The current integration of machine translation technology into human translators’ work processes is often done overly simplistic, breaks their work practices, and it is widely resisted.

Goal

The project will build the next generation translator’s workbench to improve productivity, quality, and work practices in the translation industry. Based on insights gained in the cognitive studies, novel types of assistance will be developed

Innovation

The CASMACAT project will carry out cognitive studies of actual unaltered translator behaviour based on key logging and eye tracking. The acquired data will aid understanding how interfaces with enriched information are used, help to determine translator types and styles, and to build a cognitive model of the translation process.

Based on insights gained in the cognitive studies, the project will develop novel types of assistance to human translators and integrate them into a new workbench, consisting of an editor, a server, and analysis and visualization tools. The workbench will be designed in a modular fashion and can be combined with existing computer aided translation tools.
 
The project will develop new types of assistance along the following lines:
  • Interactive translation prediction , where the CASMACAT workbench makes suggestions to the human translator how to complete the translation. The project will adapt the existing interactive machine translation paradigm by adding input modalities, especially electronic pens and basing the suggestions on better exploitation of novel statistical machine translation models, such as ones based on syntactic structure.
  • Interactive editing , where the CASMACAT workbench provides additional information about the confidence of its assistance, integrates translation memories, and assists authoring and reviewing.

Adaptive translation models , where the CASMACAT workbench learns from the interaction with the human translator by updating and adapting its models instantly based on the translation choices of the user.

The result

The CASMACAT project, in close collaboration with the MATECAT project, will develop a web-based workbench for translators targeted at the European localisation industry.

The project will demonstrate the workbench’s effectiveness in extensive field tests of real-life practice of a translation agency. In addition, the project will also reach out to the wider language service industry and online volunteer translation platforms. The outcome of the CASMACAT project will be made available as open source software to industry, academia, and to individual end users.

Impact

The proposed project will have impact on both academic research and on the translation industry. The academic impact will derive from the novel approach to building interactive MT systems: the CASMACAT methodology involves studying the behaviour of translators using MT systems, and using the resulting eye-tracking and user-activity data to inform system and user interface design.

CASMACAT’s impact on the translation industry will benefit from the fact that translator productivity and user satisfaction are at the core of the project's objectives. Both aspects are central for industrial users of translation software; if productivity gains can be demonstrated, then current market leaders are likely to incorporate insights from the CASMACAT workbench into their products. However, this also requires user acceptance, i.e., positive attitudes of professional translators towards the workbench.

 

Co-ordinator

Contact Person:

Name: Frederick Max-Lino

Tel: +44 131 650 4442

Fax: +44 131 651 4028

E-mail: Frederick.Max-Lino@ed.ac.uk

Organisation: University of Edinburgh

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