dc.contributor
Universitat Ramon Llull. La Salle
dc.contributor.author
Martín Sujo, Jessie
dc.contributor.author
Vilasis-Cardona, Xavier
dc.date.accessioned
2026-02-28T23:15:52Z
dc.date.available
2026-02-28T23:15:52Z
dc.identifier.issn
1879-8314
dc.identifier.uri
https://hdl.handle.net/20.500.14342/5990
dc.description.abstract
In correspondence with the advancement of Natural Language Processing (NLP), the field of Translation has also experienced significant advances, for example, with the use of an ecosystem for neural machine translation, called OpenNMT. However, it still has limitations, especially when it comes to translating much more specific texts. That is why this study focuses on the practical strategies that developers should follow to obtain more accurate results.
dc.relation.ispartof
Artificial Intelligence Research and Development - Proceedings of the 27th International Conference of the Catalan Association for Artificial Intelligence
dc.rights
Attribution-NonCommercial 4.0 International
dc.rights.uri
http://creativecommons.org/licenses/by-nc/4.0/
dc.subject
Natural language procesing
dc.title
Optimizing Machine Translation Models: Practical Strategies with OpenNMT
dc.type
info:eu-repo/semantics/article
dc.description.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
http://doi.org/10.3233/FAIA250582
dc.rights.accessLevel
info:eu-repo/semantics/openAccess
