Additional three Czech reference translations of the whole WMT 2011 data set (http://www.statmt.org/wmt11/test.tgz), translated from the German originals. Original segmentation of the WMT 2011 data is preserved. and This project has been sponsored by the grants GAČR P406/11/1499 and EuroMatrixPlus (FP7-ICT-2007-3-231720 of the EU and 7E09003+7E11051 of the Ministry of Education, Youth and Sports of the Czech Republic)
CzEng 1.0 is the fourth release of a sentence-parallel Czech-English corpus compiled at the Institute of Formal and Applied Linguistics (ÚFAL) freely available for non-commercial research purposes.
CzEng 1.0 contains 15 million parallel sentences (233 million English and 206 million Czech tokens) from seven different types of sources automatically annotated at surface and deep (a- and t-) layers of syntactic representation. and EuroMatrix Plus (FP7-ICT-2007-3-231720 of the EU and 7E09003+7E11051 of the Ministry of Education, Youth and Sports of the Czech Republic),
Faust (FP7-ICT-2009-4-247762 of the EU and 7E11041 of the Ministry of Education, Youth and Sports of the Czech Republic),
GAČR P406/10/P259,
GAUK 116310,
GAUK 4226/2011
Czech-Slovak parallel corpus consisting of several freely available corpora (Acquis [1], Europarl [2], Official Journal of the European Union [3] and part of OPUS corpus [4] – EMEA, EUConst, KDE4 and PHP) and downloaded website of European Commission [5]. Corpus is published in both in plaintext format and with an automatic morphological annotation.
References:
[1] http://langtech.jrc.it/JRC-Acquis.html/
[2] http://www.statmt.org/europarl/
[3] http://apertium.eu/data
[4] http://opus.lingfil.uu.se/
[5] http://ec.europa.eu/ and This work has been supported by the grant Euro-MatrixPlus (FP7-ICT-2007-3-231720 of the EU and 7E09003 of the Czech Republic)
CzEng 0.7 is a Czech-English parallel corpus compiled at the Institute of Formal and Applied Linguistics (ÚFAL), Charles University, Prague. The corpus contains no manual annotation. It is limited only to texts which have been already available in an electronic form and which are not protected by authors' rights in the Czech Republic. The main purpose of the corpus is to support Czech-English and English-Czech machine translation research with the necessary data. CzEng 0.7 consists of a large set of parallel textual documents mainly from the fields of European law, information technology, and fiction, all of them converted into a uniform XML-based file format and provided with automatic sentence alignment.
English-Slovak parallel corpus consisting of several freely available corpora (Acquis [1], Europarl [2], Official Journal of the European Union [3] and part of OPUS corpus [4] – EMEA, EUConst, KDE4 and PHP) and downloaded website of European Commission [5]. Corpus is published in both in plaintext format and with an automatic morphological annotation.
References:
[1] http://langtech.jrc.it/JRC-Acquis.html/
[2] http://www.statmt.org/europarl/
[3] http://apertium.eu/data
[4] http://opus.lingfil.uu.se/
[5] http://ec.europa.eu/ and This work has been supported by the grant Euro-MatrixPlus (FP7-ICT-2007-3-231720 of the EU and 7E09003 of the Czech Republic)
EnTam is a sentence aligned English-Tamil bilingual corpus from some of the publicly available websites that we have collected for NLP research involving Tamil. The standard set of processing has been applied on the the raw web data before the data became available in sentence aligned English-Tamil parallel corpus suitable for various NLP tasks. The parallel corpus includes texts from bible, cinema and news domains.
HindEnCorp parallel texts (sentence-aligned) come from the following sources:
Tides, which contains 50K sentence pairs taken mainly from news articles. This dataset was originally col- lected for the DARPA-TIDES surprise-language con- test in 2002, later refined at IIIT Hyderabad and provided for the NLP Tools Contest at ICON 2008 (Venkatapathy, 2008).
Commentaries by Daniel Pipes contain 322 articles in English written by a journalist Daniel Pipes and translated into Hindi.
EMILLE. This corpus (Baker et al., 2002) consists of three components: monolingual, parallel and annotated corpora. There are fourteen monolingual sub- corpora, including both written and (for some lan- guages) spoken data for fourteen South Asian lan- guages. The EMILLE monolingual corpora contain in total 92,799,000 words (including 2,627,000 words of transcribed spoken data for Bengali, Gujarati, Hindi, Punjabi and Urdu). The parallel corpus consists of 200,000 words of text in English and its accompanying translations into Hindi and other languages.
Smaller datasets as collected by Bojar et al. (2010) include the corpus used at ACL 2005 (a subcorpus of EMILLE), a corpus of named entities from Wikipedia (crawled in 2009), and Agriculture domain parallel corpus.

For the current release, we are extending the parallel corpus using these sources:
Intercorp (Čermák and Rosen,2012) is a large multilingual parallel corpus of 32 languages including Hindi. The central language used for alignment is Czech. Intercorp’s core texts amount to 202 million words. These core texts are most suitable for us because their sentence alignment is manually checked and therefore very reliable. They cover predominately short sto- ries and novels. There are seven Hindi texts in Inter- corp. Unfortunately, only for three of them the English translation is available; the other four are aligned only with Czech texts. The Hindi subcorpus of Intercorp contains 118,000 words in Hindi.
TED talks 3 held in various languages, primarily English, are equipped with transcripts and these are translated into 102 languages. There are 179 talks for which Hindi translation is available.
The Indic multi-parallel corpus (Birch et al., 2011; Post et al., 2012) is a corpus of texts from Wikipedia translated from the respective Indian language into English by non-expert translators hired over Mechanical Turk. The quality is thus somewhat mixed in many respects starting from typesetting and punctuation over capi- talization, spelling, word choice to sentence structure. A little bit of control could be in principle obtained from the fact that every input sentence was translated 4 times. We used the 2012 release of the corpus.
Launchpad.net is a software collaboration platform that hosts many open-source projects and facilitates also collaborative localization of the tools. We downloaded all revisions of all the hosted projects and extracted the localization (.po) files.
Other smaller datasets. This time, we added Wikipedia entities as crawled in 2013 (including any morphological variants of the named entitity that appears on the Hindi variant of the Wikipedia page) and words, word examples and quotes from the Shabdkosh online dictionary. and LM2010013,
IDENTIC is an Indonesian-English parallel corpus for research purposes. The corpus is a bilingual corpus paired with English. The aim of this work is to build and provide researchers a proper Indonesian-English textual data set and also to promote research in this language pair. The corpus contains texts coming from different sources with different genres. and The research leading to these results has received funding from the European Commission’s 7th Framework Program under grant agreement no 238405 (CLARA) and by the grant LC536 Centrum Komputacni Lingvistiky of the Czech Ministry of Education.