The translation task of this workshop 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.

Goals

• To investigate the applicability of current MT techniques when translating into languages other than English
• To examine special challenges in translating between European languages, including word order differences and morphology
• To create publicly available corpora for machine translation and machine translation evaluation
• To generate up-to-date performance numbers for European languages in order to provide a basis of comparison in future research
• To offer newcomers a smooth start with hands-on experience in state-of-the-art statistical machine translation methods

Changes This Year

• News Translation Only: We will only evaluate performance on a set of news stories that we prepared for this evaluation. As in the previous year, the news stories are taken from major news outlets as the BBC, Der Spiegel, Le Monde, etc. during the time period of September-October 2008. Last year's test set will serve as the development set, which we re-release in a slightly cleaned form.

• Official Metric is Manual Sentence Ranking: While we continue to experiment with different forms of manual and automatic evaluation, the official metric that we will use is human preference judgments on a sentence-by-sentence basis.

• More Training Data: The parallel corpora Europarl and News Commentary are extended, a large French-English corpus (currently 400 million words) was added, and we also proved 50-500 million word monolingual training data from the test domain of news stories.

• Constrained vs. Unconstrained: You may use any additional resources that you wish to (including training data, knowledge sources such as existing translation systems), but you should 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.

Task Description

• improve word alignment quality, phrase extraction, phrase scoring
• add new components to the open source software of the baseline system
• augment the system otherwise (e.g. by preprocessing, reranking, etc.)
• build an entirely new translation systems

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

• French-English
• Spanish-English
• German-English
• Czech-English
• Hungarian-English

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.

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.

Training Data

Additional training data is taken from the new News Commentary corpus. There are about 40-45 million words of training data per language from the Europarl corpus and 2 million words from the News Commentary corpus.

Europarl French-English Spanish-English German-English French monolingual Spanish monolingual German monolingual English monolingual

News Commentary French-English Spanish-English German-English Czech-English

News French monolingual Spanish monolingual German monolingual English monolingual Czech monolingual Hungarian monolingual

Giga-FrEn French-English Crawled from Canadian and European Union sources.

Hunglish Hungarian-English The corpus was created as part of the hunglish project by the joint work of the Media Research and Education Center at the Budapest University of Technology and Economics and the Corpus Linguistics Department at the Hungarian Academy of Sciences Institute of Linguistics.

CzEng Czech-English You will need to to download the current version of the CzEng corpus (version v0.7) from the CzEng web site.

Note that in difference to previous years the released data is not tokenized and includes sentences of any length (including empty sentences). Also, this year all data is in Unicode (UTF-8) format. The following tools allow the processing of the training data into tokenized format:

• Tokenizer tokenizer.perl
• Detokenizer detokenizer.perl
• Lowercaser lowercase.perl
• SGML Wrapper wrap-xml.perl

Development Data

News news-dev2009 English French Spanish German Czech Hungarian This data is a cleaned version of the 2008 test set.

Additional Development Data

Europarl dev2006 English French Spanish German This data is identical with the 2005 development test data and the 2006 development data.	News Commentary nc-dev2007 English French Spanish German Czech This is identical with the 2007 development data.	Hunglish hung-dev2008 Hungarian English Note that this dev set is extracted from the official Hunglish corpus. The training corpus we provide does not overlap with the dev set.
Europarl devtest2006 English French Spanish German This data is identical with the 2005 test data and the 2006 development test data.	News Commentary nc-devtest2007 English French Spanish German Czech This data is identical with the 2006 test data (out-of-domain part).	Hunglish hung-devtest2008 Hungarian English Note that this devtest set is extracted from the official Hunglish corpus. The training corpus we provide does not overlap with the devtest set.
Europarl test2006 English French Spanish German This data is identical with the 2006 test data (in-domain part).	News Commentary nc-test2007 English French Spanish German Czech This data is identical with the 2007 test data (out-of-domain part).
Europarl test2007 English French Spanish German This data is identical with the 2007 test data (in-domain part).	News Commentary nc-test2008 English French Spanish German Czech This data is identical with the 2008 test data.
Europarl test2008 English French Spanish German This data is identical with the 2008 test data.

Test Data

News news-test2009 English French Spanish German Czech Hungarian

Download

• Parallel corpus training data (541 MB)
• Giga-FrEn (729 MB) pre-release
• Giga-FrEn (1.7 GB) Release 1 (Dec 1)
• Giga-FrEn (2.3G GB) Release 2 (Dec 5)
• Monolingual language model training data (2.8 GB)
• Development sets (3.4 MB)
• Additional development sets (17 MB)
• Tools (3 KB)
• Test sets (1.2 MB) due back on December 12

Evaluation

• Manual Scoring: We will collect subjective judgments about translation quality from human annotators. If you participate in the shared task, we ask you to commit about 8 hours of time to do the manual evaluation. The evaluation will be done with an online tool.
• As in previous years, we expect the translated submissions to be in recased, detokenized, XML format, just as in most other translation campaigns (NIST, TC-Star).

Dates

supported by the EuroMatrix project, P6-IST-5-034291-STP funded by the European Commission under Framework Programme 6