This package contains data sets for development and testing of machine translation of sentences from summaries of medical articles between Czech, English, French, and German. and This work was supported by the EU FP7 project Khresmoi (European Comission contract No. 257528). The language resources are distributed by the LINDAT/Clarin project of the Ministry of Education, Youth and Sports of the Czech Republic (project no. LM2010013). We thank all the data providers and copyright holders for providing the source data and anonymous experts for translating the sentences.
This package contains data sets for development (Section dev) and testing (Section test) of machine translation of sentences from summaries of medical articles between Czech, English, French, German, Hungarian, Polish, Spanish
and Swedish. Version 2.0 extends the previous version by adding Hungarian, Polish, Spanish, and Swedish translations.
An interactive web demo for querying selected ÚFAL and LINDAT corpora. LINDAT/CLARIN KonText is a fork of ÚČNK KonText (https://github.com/czcorpus/kontext, maintained by Tomáš Machálek) that contains some modifications and additional features. Kontext, in turn, is a fork of the Bonito 2.68 python web interface to the corpus management tool Manatee (http://nlp.fi.muni.cz/trac/noske, created by Pavel Rychlý).
Statistical spell- and (occasional) grammar-checker. There are three versions: a unix command line utility and an OS X SpellServer with a System Service, that integrates with native OS X GUI applications, and a web service run by Lindat-Clarin, that can be used either through a web form in a browser, or by web applications using API. and The LINDAT-CLARIN project (LM2010013), fully supported by TheMinistry of Education, Sports and Youth of The Czech Republic under the programme LM of "Large Infrastructures"
KUK 0.0 is a pilot version of a corpus of Czech legal and administrative texts designated as data for manual and automatic assessment of accessibility (comprehensibility or clarity) of Czech legal texts.
LANGUAGES IN MIGRATION is designed as a representation of authentic spoken Czech and German that is used in informal speech (private environment, spontaneity, unpreparedness etc.) by Czech-German bilingual speakers born in Czechoslovakia around 1955 and who departed for Germany after becoming 12 years old. The corpus is composed of interviews conducted from 2018–2020 with 20 speakers on language biographies and narrated in Czech and German respectively. 10 interviews were recorded with late (German) repatriates and 10 with Czech migrants. The corpus includes transcripts of ca. 14 hours of Czech recordings and ca. 13,5 hours of German recordings. It contains 217 650 orthographic words (i.e. a total of 286 533 tokens including punctuation). Metadata of LANGUAGES IN MIGRATION include basic sociolinguistically relevant speaker categories (gender, year of birth and of migration, level of education and region of childhood and present residence).
The transcription of LANGUAGES IN MIGRATION is linked to the corresponding audio track. The transcription was carried out on the orthographic tier and supplemented by an additional metalanguage tier. The corpus LANGUAGES IN MIGRATION is lemmatized and morphologically tagged in different formats for Czech and German (Stuttgart-Tübingen-Tagset). Deviations from the norm of the spoken Czech and German of the homeland, which are understood as the result of language contact and language isolation, are tagged in a further tier both in the Czech and in the German sub-corpuses of LANGUAGES IN MIGRATION. The (anonymized) corpus is provided in form of transcripts in EAF format, which can be viewed via the freely available ELAN program, and a (semi-XML) vertical format used as an input to the Manatee query engine. The data thus correspond to the corpus available via the KonText query engine to registered users of the CNC at http://www.korpus.cz
We present a large corpus of Czech parliament plenary sessions. The corpus
consists of approximately 444 hours of speech data and corresponding text
transcriptions. The whole corpus has been segmented to short audio snippets
making it suitable for both training and evaluation of automatic speech
recognition (ASR) systems. The source language of the corpus is Czech, which
makes it a valuable resource for future research as only a few public datasets
are available for the Czech language.
"Large Scale Colloquial Persian Dataset" (LSCP) is hierarchically organized in asemantic taxonomy that focuses on multi-task informal Persian language understanding as a comprehensive problem. LSCP includes 120M sentences from 27M casual Persian tweets with its dependency relations in syntactic annotation, Part-of-speech tags, sentiment polarity and automatic translation of original Persian sentences in five different languages (EN, CS, DE, IT, HI).