Shared Task: Machine Translation

8-9 August, 2013
Sofia, Bulgaria


The recurring translation task of the WMT workshops focuses on European language pairs. Translation quality will be evaluated on a shared, unseen test set of news stories. We provide a parallel corpus as training data, a baseline system, and additional resources for download. Participants may augment the baseline system or use their own system.


The goals of the shared translation task are:

We hope that both beginners and established research groups will participate in this task.


We provide training data for five European language pairs, and a common framework (including a baseline system). The task is to improve methods current methods. This can be done in many ways. For instance participants could try to:

Participants will use their systems to translate a test set of unseen sentences in the source language. The translation quality is measured by a manual evaluation and various automatic evaluation metrics. Participants agree to contribute to the manual evaluation about eight hours of work.

You may participate in any or all of the following language pairs:

For all language pairs we will test translation in both directions. To have a common framework that allows for comparable results, and also to lower the barrier to entry, we provide a common training set and baseline system.

We also strongly encourage your participation, if you use your own training corpus, your own sentence alignment, your own language model, or your own decoder.

If you use additional training data or existing translation systems, you must flag that your system uses additional data. We will distinguish system submissions that used the provided training data (constrained) from submissions that used significant additional data resources. Note that basic linguistic tools such as taggers, parsers, or morphological analyzers are allowed in the constrained condition.

Your submission report should highlight in which ways your own methods and data differ from the standard task. We may break down submitted results in different tracks, based on what resources were used. We are mostly interested in submission that are constraint to the provided training data, so that the comparison is focused on the methods, not on the data used. You may submit contrastive runs to demonstrate the benefit of additional training data.


The provided data is mainly taken from version 7 of the Europarl corpus, which is freely available. Please click on the links below to download the sentence-aligned data, or go to the Europarl website for the source release. Note that this the same data as last year, since Europarl is not anymore translted across all 23 official European languages.

Additional training data is taken from the new News Commentary corpus. There are about 50 million words of training data per language from the Europarl corpus and 3 million words from the News Commentary corpus.

A new data resource this year is the Common Crawl corpus which was collected from web sources. Each parallel corpus comes with a annotation file that gives the source of each sentence pair.

You may also use the following monolingual corpora released by the LDC:

Note that the released data is not tokenized and includes sentences of any length (including empty sentences). All data is in Unicode (UTF-8) format. The following tools allow the processing of the training data into tokenized format:

These tools are available in the Moses git repository.


To evaluate your system during development, we suggest using the 2012 test set. The data is provided in raw text format and in an SGML format that suits the NIST scoring tool. We also release other test sets from previous years.

News news-test2008
  • English
  • French
  • Spanish
  • German
  • Czech
  • Hungarian
Cleaned version of the 2008 test set.
2051 sentences.
News news-test2009
  • English
  • French
  • Spanish
  • German
  • Czech
  • Hungarian
  • Italian
2525+502 sentences.
News news-test2010
  • English
  • French
  • Spanish
  • German
  • Czech
2489 sentences.
News news-test2011
  • English
  • French
  • Spanish
  • German
  • Czech
3003 sentences.
News news-test2012
  • English
  • French
  • Spanish
  • German
  • Czech
  • Russian
3003 sentences.

The news-test2011 set has three additional Czech translations that you may want to use. You can download them from Charles University.



Punctuation in the official test sets will be encoded with ASCII characters (not complex Unicode characters) as much as possible. You may want to normalize your system's output before submission. You are able able to use a rawer version of the test sets that does not have this normalization.

To submit your results, please first convert into into SGML format as required by the NIST BLEU scorer, and then upload it to the website

SGML Format

Each submitted file has to be in a format that is used by standard scoring scripts such as NIST BLEU or TER.

This format is similar to the one used in the source test set files that were released, except for:

The script wrap-xml.perl makes the conversion of a output file in one-segment-per-line format into the required SGML file very easy:

Example: wrap-xml.perl en Google < decoder-output > decoder-output.sgm

Upload to Website

Upload happens in three easy steps:

  1. Go to the website
  2. Create an account under the menu item Account -> Create Account.
  3. Go to Account -> upload/edit content, and follow the link "Submit a system run"

If you are submitting contrastive runs, please submit your primary system first and mark it clearly as the primary submission.


Evaluation will be done both automatically as well as by human judgement.


Release of translation task training dataEarly February 2013
Release of translation task test setApril 29, 2013
Submission deadline for translation taskMay 3 2013
Release of quality estimation task training dataFebruary 28 2013
Release of quality estimation task test dataMay 25, 2013
Release of system outputs for metrics taskMay 10, 2013
Submission deadline for metrics task and quality estimation taskMay 31, 2013
Manual evaluation periodMay 17, 2013 - June 7, 2013

Supported by the European Commision
under the
project (grant number 288487)