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Leveraging mouse tracking data for part-of-speech and syntactic dependency prediction in Albanian

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3AC3A3WAH3" target="_blank" >RIV/00216208:11320/26:C3A3WAH3 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1145/3715669.3726840" target="_blank" >http://dx.doi.org/10.1145/3715669.3726840</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1145/3715669.3726840" target="_blank" >10.1145/3715669.3726840</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Leveraging mouse tracking data for part-of-speech and syntactic dependency prediction in Albanian

  • Original language description

    High-quality eye-tracking equipment plays an important role in understanding reading behaviors and linguistic processes, such as part-of-speech (PoS) tagging and syntactic dependency parsing. However, this technology is expensive, and data is not always available for under represented languages, such as Albanian. The expense and lack of appropriate equipment makes it difficult to conduct research in reading behavior in Albanian but not only. To address this limitation, we explore the usage of low-cost alternatives to study reading behaviors. Specifically, we leverage mouse tracking data to improve the accuracy of computational linguistic models that predict PoS and syntactic dependencies. The preliminary results from our study suggest that the addition of mouse tracking data, particularly reading time, significantly improves the performance of various linguistic prediction models. These findings emphasizes that mouse tracking data combined with annotated texts provides a viable solution to enhance existing models for low resource languages like Albanian. © 2025 Copyright held by the owner/author(s).

  • 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

  • Continuities

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

    Eye Track. Res. Appl. Symp. (ETRA)

  • ISBN

    979-8-4007-1487-0

  • ISSN

  • e-ISSN

  • Number of pages

    27

  • Pages from-to

    115

  • Publisher name

    Association for Computing Machinery

  • Place of publication

  • Event location

    Tokyo

  • Event date

    Jan 1, 2026

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article