Spoken Spanish PoS tagging: gold standard dataset

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AMF98BC5I" target="_blank" >RIV/00216208:11320/25:MF98BC5I - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197288516&doi=10.1007%2fs10579-024-09751-x&partnerID=40&md5=48167acf48572b979c669b95b43a9a03" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197288516&doi=10.1007%2fs10579-024-09751-x&partnerID=40&md5=48167acf48572b979c669b95b43a9a03</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10579-024-09751-x" target="_blank" >10.1007/s10579-024-09751-x</a>

Result language
angličtina
Original language name
Spoken Spanish PoS tagging: gold standard dataset
Original language description
The development of a benchmark for part-of-speech (PoS) tagging of spoken dialectal European Spanish is presented, which will serve as the foundation for a future treebank. The benchmark is constructed using transcriptions of the Corpus Oral y Sonoro del Español Rural (COSER;“Audible corpus of spoken rural Spanish”) and follows the Universal Dependencies project guidelines. We describe the methodology used to create a gold standard, which serves to evaluate different state-of-the-art PoS taggers (spaCy, Stanza NLP, and UDPipe), originally trained on written data and to fine-tune and evaluate a model for spoken Spanish. It is shown that the accuracy of these taggers drops from 0.98-0.99 to 0.94-0.95 when tested on spoken data. Of these three taggers, the spaCy’s trf (transformers) and Stanza NLP models performed the best. Finally, the spaCy trf model is fine-tuned using our gold standard, which resulted in an accuracy of 0.98 for coarse-grained tags (UPOS) and 0.97 for fine-grained tags (FEATS). Our benchmark will enable the development of more accurate PoS taggers for spoken Spanish and facilitate the construction of a treebank for European Spanish varieties. © The Author(s) 2024.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
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)

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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