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)
Corpus AKCES 4 includes texts written in czech by youth growing up in locations at risk of social exclusion (AKCES/CLAC - Czech Language Acquisition Corpora) and ESF (OPVK CZ.1.07/2.2.00/07.0259), MŠMT (MSM0021620825), UK (P10)
Essays written by non-native learners of Czech, a part of AKCES/CLAC – Czech Language Acquisition Corpora. CzeSL-SGT stands for Czech as a Second Language with Spelling, Grammar and Tags. Extends the “foreign” (ciz) part of AKCES 3 (CzeSL-plain) by texts collected in 2013. Original forms and automatic corrections are tagged, lemmatized and assigned erros labels. Most texts have metadata attributes (30 items) about the author and the text.
Essays written by non-native learners of Czech, a part of AKCES/CLAC – Czech Language Acquisition Corpora. CzeSL-SGT stands for Czech as a Second Language with Spelling, Grammar and Tags. Extends the “foreign” (ciz) part of AKCES 3 (CzeSL-plain) by texts collected in 2013. Original forms and automatic corrections are tagged, lemmatized and assigned erros labels. Most texts have metadata attributes (30 items) about the author and the text.
In addition to a few minor bugs, fixes a critical issue in Release 1: the native speakers of Ukrainian (s_L1:"uk") were wrongly labelled as speakers of "other European languages" (s_L1_group="IE"), instead of speakers of a Slavic language (s_L1_group="S"). The file is now a regular XML document, with all annotation represented as XML attributes.
AKCES-GEC is a grammar error correction corpus for Czech generated from a subset of AKCES. It contains train, dev and test files annotated in M2 format.
Note that in comparison to CZESL-GEC dataset, this dataset contains separated edits together with their type annotations in M2 format and also has two times more sentences.
If you use this dataset, please use following citation:
@article{naplava2019wnut,
title={Grammatical Error Correction in Low-Resource Scenarios},
author={N{\'a}plava, Jakub and Straka, Milan},
journal={arXiv preprint arXiv:1910.00353},
year={2019}
}
CzeSL-GEC is a corpus containing sentence pairs of original and corrected versions of Czech sentences collected from essays written by both non-native learners of Czech and Czech pupils with Romani background. To create this corpus, unreleased CzeSL-man corpus (http://utkl.ff.cuni.cz/learncorp/) was utilized. All sentences in the corpus are word tokenized.
FicTree is a dependency treebank of Czech fiction manually annotated in the format of the analytical layer of the Prague Dependency Trebank. The treebank consists of 12,760 sentences (166,432 tokens). The texts come from eight literary works published in the Czech Republic between 1991 and 2007. The syntactic annotation of the treebank was first performed by two distinct parsers (MSTParser and MaltParser) trained on the PDT training data, then manually corrected. Any differences between the two versions were resolved manually (by another annotator).
The corpus is provided in a vertical format, where sentence boundaries are marked with a blank line. Every word form is written on a separate line, followed by five tab-separated attributes: lemma, tag, ID (word index in the sentence), head and deprel (analytical function, afun in the PDT formalism). The texts are shuffled in random chunks of maximum 100 words (respecting sentence boundaries). Each chunk is provided as a separate file, with the suggested division into train, dev and test sets written as file prefix.
ORTOFON v3 is a corpus of authentic spoken Czech used in informal situations (private environment, spontaneity, unpreparedness etc.) that covers the area of the whole Czech Republic. The corpus is composed of 697 recordings from 2012–2020 and contains 2 445 793 orthographic words (i.e. a total of 2 976 742 tokens including punctuation); a total of 1 121 different speakers appear in the probes. ORTOFON v3 is partially balanced regarding the basic sociolinguistic speaker categories (gender, age group, level of education and region of childhood residence). The transcription is linked to the corresponding audio track. Unlike the ORAL-series corpora, the transcription was carried out on two main tiers, orthographic and phonetic, supplemented by an additional metalanguage tier. The (anonymized) transcriptions are provided in the XML Elan Annotation format, audio (with corresponding anonymization beeps) is in uncompressed 16-bit PCM WAV, mono, 16 kHz format. Another format option of the transcriptions is also available under less restrictive CC BY-NC-SA license at http://hdl.handle.net/11234/1-5687
ORTOFON v3 is a corpus of authentic spoken Czech used in informal situations (private environment, spontaneity, unpreparedness etc.) that covers the area of the whole Czech Republic. The corpus is composed of 697 recordings from 2012–2020 and contains 2 445 793 orthographic words (i.e. a total of 2 976 742 tokens including punctuation); a total of 1 121 different speakers appear in the probes. ORTOFON v3 is partially balanced regarding the basic sociolinguistic speaker categories (gender, age group, level of education and region of childhood residence). The transcription is linked to the corresponding audio track. Unlike the ORAL-series corpora, the transcription was carried out on two main tiers, orthographic and phonetic, supplemented by an additional metalanguage tier. ORTOFON v3 is lemmatized and morphologically tagged according to the SYN2020 standard. This was performed with special attention paid to the specificity of the informal spoken Czech and includes also spoken training data. The (anonymized) corpus is provided in 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 Please note: this item includes only the transcriptions, audio (and the transcripts in their original format) is available under more restrictive non-CC license at http://hdl.handle.net/11234/1-5686