D 2013

A learner corpus of Czech: Current state and future directions.

ŠKODOVÁ, Svatava; Barbora ŠTINDLOVÁ; Alexandr ROSEN and Jiří HANA

Basic information

Original name

A learner corpus of Czech: Current state and future directions.

Authors

ŠKODOVÁ, Svatava (203 Czech Republic, belonging to the institution); Barbora ŠTINDLOVÁ (203 Czech Republic, belonging to the institution); Alexandr ROSEN (203 Czech Republic) and Jiří HANA (203 Czech Republic)

Edition

Louvain-la-Neuve, Twenty Years of Learner Corpus Research: Looking back, Moving ahead. Corpora and Language in Use – Proceedings 1, p. 435-446, 12 pp. 2013

Publisher

Presses universitaires de Louvain

Other information

Language

English

Type of outcome

Proceedings paper

Field of Study

60200 6.2 Languages and Literature

Confidentiality degree

is not subject to a state or trade secret

Publication form

printed version "print"

References:

URL

RIV identification code

RIV/46747885:24510/13:#0001080

Organization

Faculty of Science, Humanities and Education – Technical University of Liberec – Repository

ISBN

978-2-87558-199-0

Keywords in English

multi-level annotation
Changed: 10/3/2015 13:50, RNDr. Daniel Jakubík

Abstract

In the original language

The paper describes CzeSL, a learner corpus of Czech, together with basic properties of its design. It starts with a brief introduction of the project within the context of AKCES, a programme addressing Czech acquisition corpora; in connection with the programme we are also concerned with groups of respondents, including differencies due to their L1; further we comment on the choice of sociocultural metadata recorded with each text and related both to the learner and the text production task. Next we describe the intended uses of CzeSL. The main parts of the text deal with transcription and annotation. We explain the issues involved in transcrition of the handwritten texts and present the concept of a multi-level annotation scheme including taxonomy of captured errors. We conclude by mentioning results from an evaluation of the error annotation and presenting plans for future research.
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