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Refining Czech GEC: Insights from a Multi-experiment Approach

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A10511642" target="_blank" >RIV/00216208:11320/25:10511642 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/chapter/10.1007/978-3-032-02551-7_7" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-032-02551-7_7</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-032-02551-7_7" target="_blank" >10.1007/978-3-032-02551-7_7</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Refining Czech GEC: Insights from a Multi-experiment Approach

  • Original language description

    We present a grammar error correction (GEC) system that achieves state of the art for the Czech language. Our system is based on a neural network translation approach with the Transformer architecture, and its key feature is its real-time synthetic generation pipeline, which dynamically augments sentences with artificial errors by introducing both language-agnostic and Czech-specific errors. We conduct a comprehensive series of experiments, investigating the Czech GEC corpora as bases for synthetic error introduction, several error generation strategies, domain balancing, tokenization granularity, model size, and data scaling during fine-tuning. Additionally, we evaluate the performance of large language models (LLMs) on Czech GEC in both end-user and expert fine-tuning scenarios. Our best-performing model is superior both in performance and computational efficiency. The source code and the trained model links are available on https://github.com/ufal/tsd2025-gec.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/EH23_020%2F0008518" target="_blank" >EH23_020/0008518: Linguistics, Artificial Intelligence and Language and Speech Technologies: from Research to Applications</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2025

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    28th International Conference on Text, Speech and Dialogue (Part II)

  • ISBN

    978-3-032-02551-7

  • ISSN

  • e-ISSN

  • Number of pages

    13

  • Pages from-to

    64-76

  • Publisher name

    Springer

  • Place of publication

    Cham, Switzerland

  • Event location

    Erlangen, Germany

  • Event date

    Aug 25, 2025

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    001576349100006