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Automatic Identification of Learners' Language Background based on their Writing in Czech

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F13%3A10194613" target="_blank" >RIV/00216208:11320/13:10194613 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Automatic Identification of Learners' Language Background based on their Writing in Czech

  • Original language description

    The goal of this study is to investigate whether learners' written data in highly inflectional Czech can suggest a consistent set of clues for automatic identification of the learners' L1 background. For our experiments, we use texts written by learnersof Czech, which have been automatically and manually annotated for errors. We define two classes of learners: speakers of Indo-European languages and speakers of non-Indo-European languages. We use an SVM classifier to perform the binary classification.We show that non-content based features perform well on highly inflectional data. In particular, features reflecting errors in orthography are the most useful, yielding about 89% precision and the same recall. A detailed discussion of the best performingfeatures is provided.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GPP406%2F10%2FP328" target="_blank" >GPP406/10/P328: Resource-light Morphological Analysis and Tagging</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2013

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 6th International Joint Conference on Natural Language Processing

  • ISBN

    978-4-9907348-0-0

  • ISSN

  • e-ISSN

  • Number of pages

    9

  • Pages from-to

    1428-1436

  • Publisher name

    Asian Federation of Natural Language Processing

  • Place of publication

    Nagoya, Japan

  • Event location

    Nagoya, Japan

  • Event date

    Oct 14, 2013

  • Type of event by nationality

    CST - Celostátní akce

  • UT code for WoS article