Transformer-Based Approaches for Purépecha Translation: Advancing Indigenous Language Preservation

Abstract

Abstract. Indigenous languages like Purépecha face significant challenges in the modern era, particularly due to limited digital resources and a dwindling number of speakers. This study, conducted by researchers from CIC-IPN and CONACYT, presents an innovative application of transformer-based neural networks for the automatic translation of Purépecha to Spanish. Unlike previous works that utilized transformer architectures, this work develops a unique bilingual corpus through an algorithm based on the verbal inflection of Purépecha verbs, generating simple sentences in Purépecha and their corresponding Spanish translations. This corpus was then used to train a transformer model for automatic translation. The results indicate the potential of artificial intelligence to contribute to the preservation and revitalization of indigenous languages, opening new possibilities in the field of automatic translation and other natural language processing sectors.keywords in this section.