EMNLP 2015

17-18 September 2015
Lisbon, Portugal


This workshop builds on nine previous workshops on statistical machine translation:


Release of training data for translation taskEarly January, 2015
Release of training data for automatic post-editing taskJanuary 31, 2015
Release of MT system for tuning taskFebruary 9, 2015
Release of training data for quality estimation taskFebruary 15, 2015
Registration for complimentary manual evaluation (tuning task)February 22, 2015
Submission deadline for tuning taskApril 20, 2015
Test set distributed for translation taskApril 20, 2015
Submission deadline for translation taskApril 27, 2015
Test set distributed automatic post-editing taskApril 27, 2015
System outputs distributed for metrics taskMay 4, 2015
Test sets distributed for quality estimation taskMay 4, 2015
Submission deadline for automatic post-editing taskMay 15, 2015
Submission deadline for metrics taskMay 25, 2015
Submission deadline for quality estimation taskJune 2nd, 2015
Start of manual evaluation periodMay 4, 2015
End of manual evaluationJune 8, 2015
Paper submission deadlineJune 28, 2015
Notification of acceptanceJuly 21, 2015
Camera-ready deadlineAugust 11, 2015


This year's workshop will feature five shared tasks:

In addition to the shared tasks, the workshop will also feature scientific papers on topics related to MT. Topics of interest include, but are not limited to:

We encourage authors to evaluate their approaches to the above topics using the common data sets created for the shared tasks.


The first shared task which will examine translation between the following language pairs:

The text for all the test sets will be drawn from news articles except for (NEW) the French-English set, which will be drawn from user-generated comments on the news articles. Participants may submit translations for any or all of the language directions. In addition to the common test sets the workshop organizers will provide optional training resources, including a newly expanded release of the Europarl corpora and out-of-domain corpora.

All participants who submit entries will have their translations evaluated. We will evaluate translation performance by human judgment. To facilitate the human evaluation we will require participants in the shared tasks to manually judge some of the submitted translations. For each team, this will amount to ranking 300 sets of 5 translations, per language pair submitted.

We also provide baseline machine translation systems, with performance comparable to the best systems from last year's shared task.


This shared task will examine automatic methods for correcting errors produced by machine translation (MT) systems. Automatic Post-editing (APE) aims at improving MT output in black box scenarios, in which the MT system is used "as is" and cannot be modified. From the application point of view APE components would make it possible to:

In this first edition of the task, the evaluation will focus on one language pair (English-Spanish), measuring systems' capability to reduce the distance (HTER) that separates an automatic translation from its human-revised version approved for publication. Training and test data are provided by Unbabel.


Quality estimation systems aim at producing an estimate on the quality of a given translation at system run-time, without access to a reference translation. This topic is particularly relevant from a user perspective. Among other applications, it can (i) help decide whether a given translation is good enough for publishing as is; (ii) filter out sentences that are not good enough for post-editing; (iii) select the best translation among options from multiple MT and/or translation memory systems; (iv) inform readers of the target language of whether or not they can rely on a translation; and (v) spot parts (words or phrases) of a translation that are potentially incorrect.

Research on this topic has been showing promising results in the last couple of years. Building on the last three years' experience, the Quality-Estimation track of the WMT15 workshop and shared-task will focus on English, Spanish and German as languages and provide new training and test sets, along with evaluation metrics and baseline systems for variants of the task at three different levels of prediction: word, sentence, and document.


The metrics task (also called evaluation task) will assess automatic evaluation metrics' ability to:

Participants in the shared evaluation task will use their automatic evaluation metrics to score the output from the translation task and the tunable metrics task. In addition to MT outputs from the other two tasks, the participants will be provided with reference translations. We will measure the correlation of automatic evaluation metrics with the human judgments.


In the tuning task is a follow up of WMT11 invitation-only tunable metrics task. The task will assess your team's ability to optimize the parameters of a given hierarchical MT system (Moses).

Participants in the tuning task will be given complete Moses models for English-to-Czech and Czech-to-English translation and the standard developments sets from the translation task. The participants are expected to submit the moses.ini for one or both of the translation directions. We will use the configuration and a fixed revision of Moses to translate official WMT15 test set. The outputs of the various configurations of the system will be scored using the standard manual evaluation procedure.


Submissions will consist of regular full papers of 6-10 pages, plus additional pages for references, formatted following the EMNLP 2015 guidelines. In addition, shared task participants will be invited to submit short papers (4-6 pages) describing their systems or their evaluation metrics. Both submission and review processes will be handled electronically. Note that regular papers must be anonymized, while system descriptions do not need to be.

We encourage individuals who are submitting research papers to evaluate their approaches using the training resources provided by this workshop and past workshops, so that their experiments can be repeated by others using these publicly available corpora.


For details on posters, please check with the local organisers.


Subscribe to to the announcement list for WMT by entering your e-mail address below. This list will be used to announce when the test sets are released, to indicate any corrections to the training sets, and to amend the deadlines as needed.

You can read past announcements on the Google Groups page for WMT. These also include an archive of annoucements from earlier workshops. Google Groups


Jacob Devlin (Microsoft Research)
A Practical Guide to Real-Time Neural Translation


Ondřej Bojar (Charles University in Prague)
Rajan Chatterjee (FBK)
Christian Federmann (MSR)
Barry Haddow (University of Edinburgh)
Chris Hokamp (Dublin City University)
Matthias Huck (University of Edinburgh)
Varvara Logacheva (University of Sheffield)
Pavel Pecina (Charles University in Prague)
Philipp Koehn (University of Edinburgh / Johns Hopkins University)
Christof Monz (University of Amsterdam)
Matteo Negri (FBK)
Matt Post (Johns Hopkins University)
Carolina Scarton (University of Sheffield)
Lucia Specia (University of Sheffield)
Marco Turchi (FBK)



For general questions, comments, etc. please send email to bhaddow@inf.ed.ac.uk.
For task-specific questions, please contact the relevant organisers.


WMT15 receives support from the European Union under the projects MosesCore (grant number 288487), Cracker and QT21.
We thank Yandex for their donation of data for the Russian-English task.