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
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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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
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e-ISSN
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Number of pages
27
Pages from-to
115
Publisher name
Association for Computing Machinery
Place of publication
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Event location
Tokyo
Event date
Jan 1, 2026
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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