Findings of the WMT 2024 Shared Task Translation into Low-Resource Languages of Spain: Blending Rule-Based and Neural Systems

Felipe Sánchez-Martínez, Juan Antonio Pérez-Ortiz, Aarón Galiano Jiménez, Antoni Oliver

Abstract: This paper presents the results of the Ninth Conference on Machine Translation (WMT24) Shared Task “Translation into Low-Resource Languages of Spain”’. The task focused on the development of machine translation systems for three language pairs: Spanish-Aragonese, Spanish-Aranese, and Spanish-Asturian. 17 teams participated in the shared task with a total of 87 submissions. The baseline system for all language pairs was Apertium, a rule-based machine translation system that still performs competitively well, even in an era dominated by more advanced non-symbolic approaches. We report and discuss the results of the submitted systems, highlighting the strengths of both neural and rule-based approaches.