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Subject: [ E-CFP ] Call for papers: QTLaunchPad Workshop on User-Centric Machine Translation &, Evaluation at MT Summit XIV
From: <mlf_(on)_ua.es>
Date received: 02 Mar 2013
Deadline: 14 Jun 2013
Start date: 03 Sep 2013





QTLaunchPad Workshop on User-Centric Machine Translation &

Evaluation at MT Summit XIV, Nice, September 3rd, 2013

Call for Papers

With the uptake of MT in production workflows, the issues of
usability and realistic assessment of MT quality have led to
increased calls for user-centric approaches to evaluation,
accessibility, and effective usage. Users and their feedback are
vital at many key points in the MT process: ranging from sourcing
and using data, developing systems, evaluating them and their
output, through to end-user consumption.

Users come in many forms: translators, post-editors, developers,
and evaluators, and the quality of the tools, methods, and
resources available to them are of critical importance,
especially in the context of high-quality MT. There is a growing
need for appropriate tools and resources to support MT in this
regard to go beyond the crude scores of one-size-fits-all
standard automatic metrics and resource-heavy human evaluation. A
top desideratum is to enhance the diagnostic value of MT
evaluation in order to help developers fine-tune and optimise the
performance of their systems and to prepare the systems for
actual usage in production environments.

This full-day workshop consists of an opening keynote by Philipp
Koehn (University of Edinburgh), followed by a thematic series of
presentations around the topics listed below. We then focus on
the Barriers to High-Quality Machine Translation, a central
concern of the QTLaunchPad project. This forms the basis of an
interactive panel discussion comprised of invited representatives
from industry, the translation community, researchers, government
users, and the project consortium.

Topics of Interest:

    User-centric measures and usability studies, e.g. methods of
    MT evaluation, cognitive effort, user experience and
    performance.

    Crowd and cloud ventures, e.g. crowd-sourced data,
    cloud-based translation and evaluation.

    Corpora for MT development and evaluation, e.g. availability,
    preprocessing, quality, interoperability, annotation, error
    corpora and test suites, self-learning, adaptive MT, feedback
    mechanisms.

    Diagnostic MT evaluation - human in the loop, e.g.
    identification and auto-correction of recurrent errors,
    learning from human evaluation.

    Fully and semi-automated error solutions, e.g. below
    threshold medium-quality translations, identifying and
    overcoming quality barriers.

Schedule:

Call for Papers

1st of March, 2013

Submission of Papers

14th of June, 2013

Author Notifications

5th of July, 2013

Final/Camera-Ready Version

1st of August, 2013

QTLaunchPad Workshop

3rd of September, 2013

MT Summit Main Conference

4-6th of September, 2013

Submissions: EasyChair

Contact: stephen.doherty_(at)_dcu.ie

Programme Committee:

Hala Almaghout, CNGL Dublin City University

Silvia Bernardini, University of Bologna at Forlì

Lynne Bowker, University of Ottawa

Adriano Ferraresi, University of Bologna at Forlì

Markus Foti, Directorate General for Translation

Federico Gaspari, CNGL Dublin City University

Josef van Genabith, CNGL Dublin City University

Declan Groves, CNGL Dublin City University

Dorothy Kenny, SALIS Dublin City University

Qun Liu, CNGL Dublin City University

Arle Lommel, Deutsche Forschungszentrum für Künstliche
Intelligenz

Joss Moorkens, CNGL Dublin City University

Maja Popovic, Deutsche Forschungszentrum für Künstliche
Intelligenz

Johann Roturier, Symantec

Antonio Toral, CNGL Dublin City University

Hans Uszkoreit, Deutsche Forschungszentrum für Künstliche
Intelligenz

Eros Zanchetta, University of Bologna at Forlì

Federico Zanettin, University of Perugia

Ventsislav Zhechev, Autodesk

Workshop Organisers:

Stephen Doherty, CNGL Dublin City University

Lucia Specia, University of Sheffield

David Vilar, Deutsche Forschungszentrum für Künstliche
Intelligenz

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