Estudio de la cortesía en traducción automática neuronalmodelos ajustados y modelos multirregistro para el castellano

  1. Aranberri, Nora
  2. Soler Uguet, Celia
Revista:
Procesamiento del lenguaje natural

ISSN: 1135-5948

Año de publicación: 2023

Número: 70

Páginas: 199-212

Tipo: Artículo

DIALNET GOOGLE SCHOLAR lock_openRUA editor

Otras publicaciones en: Procesamiento del lenguaje natural

Resumen

En la actualidad, la traducción automática neuronal es capaz de generar traducciones de alta calidad en lo que respecta a la precisión gramatical y la fluidez. Así, es hora de ampliar los objetivos de investigación y considerar aspectos de la lengua que van más allá de los atributos mencionados para seguir superando los límites de la tecnología. En este trabajo, nos centramos en la cortesía. En concreto, adaptamos y exploramos, para el castellano, dos enfoques diferentes de adaptación al dominio: modelos ajustados y modelos multilingües. Los resultados de las evaluaciones automáticas y manuales parecen indicar que el segundo podría ser mejor para lograr un equilibrio de calidad entre todos los registros (formal, informal y neutro). El ajuste de modelos parece sufrir de olvido catastrófico, lo que conduce a un peor rendimiento general de los motores.

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