dc.contributor.author | López Zorrilla, Asier | |
dc.contributor.author | deVelasco Vázquez, Mikel | |
dc.contributor.author | Justo Blanco, Raquel | |
dc.date.accessioned | 2020-06-30T10:51:28Z | |
dc.date.available | 2020-06-30T10:51:28Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Ekaia 37 : 327-341 (2020) | |
dc.identifier.issn | 0214-9001 | |
dc.identifier.uri | http://hdl.handle.net/10810/44749 | |
dc.description.abstract | This work presents a neural dialogue system capable of learning Basque. To this end, we build upon generative adversarial networks which implement the idea of the Turing test. We demonstrate that training such a dialogue system with corpora two orders of magnitude smaller than usual English corpora is feasible. Finally, we also found that preprocessing the Basque language according to its morphology helps training these neural models. To the best of our knowledge, this is the first attempt to develop a neural dialogue system in Basque.; Lan honetan sare neuronalen bidez euskaraz hitz egiten ikasten duen elkarrizketa sistema automatikoa aurkezten dugu. Horretarako, Turingen testaren ideia era konputazionalean inplementatzen duten sare neuronal sortzaile aurkariak erabili ditugu. Normalean erabiltzen diren ingelesezko corpusak baino bi magnitude ordena txikiagoa den euskarazko corpus batekin halako sareak entrenatzea badagoela frogatzen dugu. Amaitzeko, euskararen morfologia kontuan hartzen duen aurreprozesamendua erabiltzea komenigarria dela erakusten dugu. Dakigunaren arabera, sare neuronaletan oinarrituta dagoen euskarazko lehen elkarrizketa sistema aurkezten dugu. | |
dc.language.iso | eus | |
dc.publisher | Servicio Editorial de la Universidad del País Vasco/Euskal Herriko Unibertsitatearen Argitalpen Zerbitzua | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | |
dc.title | Euskarazko elkarrizketa sistema automatikoa sare neuronalen bidez | |
dc.type | info:eu-repo/semantics/article | |
dc.rights.holder | © 2020 UPV/EHU Attribution-NonCommercial-ShareAlike 4.0 International | |
dc.identifier.doi | 10.1387/ekaia.20987 | |