Summary of the paper
| Title | DCEP -Digital Corpus of the European Parliament |
|---|---|
| Authors | Najeh Hajlaoui, David Kolovratnik, Jaakko Väyrynen, Ralf Steinberger and Daniel Varga |
| Abstract | We are presenting a new highly multilingual document-aligned parallel corpus called DCEP - Digital Corpus of the European Parliament. It consists of various document types covering a wide range of subject domains. With a total of 1.37 billion words in 23 languages (253 language pairs), gathered in the course of ten years, this is the largest single release of documents by a European Union institution. DCEP contains most of the content of the European Parliament's official Website. It includes different document types produced between 2001 and 2012, excluding only the documents already exist in the Europarl corpus to avoid overlapping. We are presenting the typical acquisition steps of the DCEP corpus: data access, document alignment, sentence splitting, normalisation and tokenisation, and sentence alignment efforts. The sentence-level alignment is still in progress but based on some first experiments; we showed that DCEP is very useful for NLP applications, in particular for Statistical Machine Translation. |
| Topics | Machine Translation, SpeechToSpeech Translation, Lexicon, Lexical Database |
Full paper  |
DCEP -Digital Corpus of the European Parliament |
| Bibtex | @InProceedings{HAJLAOUI14.943, author = {Najeh Hajlaoui and David Kolovratnik and Jaakko Väyrynen and Ralf Steinberger and Daniel Varga}, title = {DCEP -Digital Corpus of the European Parliament}, booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)}, year = {2014}, month = {may}, date = {26-31}, address = {Reykjavik, Iceland}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, isbn = {978-2-9517408-8-4}, language = {english} } |