The application, developed in C#, automatically identifies the language of a text written in one of the 21 European Union languages. By using training texts in different languages (approx. 1.5Mb of text for each language), a training module counts the prefixes (the first 3 characters) and the suffixes (4 characters endings) for all the words in the texts, for each language. For every language two models are constructed, containing the weights (percentages) of prefixes and suffixes in the texts representing a language. In the prediction phase, for a new text, two models are built on the fly in a similar manner. These models are then compared with the stored models representing each language for which the application was trained. Using comparison functions, the best model is chose. More detailed descriptions are available in [[http://www.racai.ro/~tufis/papers|the following papers]]: -- Dan Tufiş, Radu Ion, Alexandru Ceauşu, and Dan Ştefănescu (2008). RACAI's Linguistic Web Services. In Proceedings of the 6th Language Resources and Evaluation Conference - LREC 2008, Marrakech, Morocco, May 2008. ELRA - European Language Resources Association. ISBN 2-9517408-4-0. -- Dan Tufiş and Alexandru Ceauşu (2007). Diacritics Restoration in Romanian Texts. In Elena Paskaleva and Milena Slavcheva (eds.), A Common Natural Language Processing Paradigm for Balkan Languages - RANLP 2007 Workshop Proceedings, pp. 49-56, Borovets, Bulgaria, September 2007. INCOMA Ltd., Shoumen, Bulgaria. ISBN 978-954-91743-8-0. -- Dan Tufiş and Adrian Chiţu (1999). Automatic Insertion of Diacritics in Romanian Texts. In Ferenc Kiefer, Gábor Kiss, and Júlia Pajzs (eds.), Proceedings of the 5th International Workshop on Computational Lexicography (COMPLEX 1999), pp. 185-194, Pecs, Hungary, May 1999. Linguistics Institute, Hungarian Academy of Sciences.
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)
This xml file describes the Arabic phonetic constraints are to be applied on Arabic root. The first rule category lists the letters that may not occur in the same root, regardless of their order. The second category lists the letters that may not be used together in a root word with a specific order. The third and fourth categories show that each contiguous letters must not be redundant
ISLRN: 991-445-325-823-5
Lexical network AdjDeriNet consists of pairs of base adjectives and their derivatives. It contains nearly 18 thousand base adjectives that are base words for more than 26 thousand lexemes of several parts of speech.
Corpus contains recordings of communication between air traffic controllers and pilots. The speech is manually transcribed and labeled with the information about the speaker (pilot/controller, not the full identity of the person). The corpus is currently small (20 hours) but we plan to search for additional data next year. The audio data format is: 8kHz, 16bit PCM, mono. and Technology Agency of the Czech Republic, project No. TA01030476.
Corpus AKCES 2 consists of trancripts of recordings of classes at Czech elementary and secondary schools (AKCES/CLAC - Czech Language Acquisition Corpora). It is the same data as the corpus "Schola 2010" (see the link for search), but all the proper names have been removed in order to protect the privacy of participants. and MŠMT (MSM0021620825), UK (PRVOUK P 10)
Corpus AKCES 2 ver. 2 consists of full, unabridged trancripts of recordings of classes at Czech elementary and secondary schools (AKCES/CLAC - Czech Language Acquisition Corpora). It is the same data as the corpus "Schola 2010" (see the link for search), but all the proper names have been removed in order to protect the privacy of participants. and UK, PRVOUK P10
Corpus AKCES 3 includes texts written in czech by non-native speakers (AKCES/CLAC - Czech Language Acquisition Corpora) and ESF (OPVK CZ.1.07/2.2.00/07.0259), MŠMT (MSM0021620825), UK (P10)