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Conference contributions 1
ARTIFICIAL INTELLIGENCE IN LEARNING TRANSLATION:
A perspective from cognitive linguistics
The fast development of artificial intelligence (AI) has helped language learners to use AI Bots to help them with translation work, but simultaneously but has simultaneously made them depend heavily on the tools, and the translation quality remains inconsistent due to linguistic, cultural, and contextual disparities. From the perspective of cognitive linguistics, language learners need to incorporate conceptual blending and metaphorical mappings across languages using intralingual rewording or interlingual rephrasing. Cognitive linguistics focuses on the meaning coming from the interaction between language, thought, and cultural context, while AI Bots rely solely on vast corpora and modeling to interpret language structures provided. The study investigates how language learners use AI Bots in helping with translation work. This study presents the use of AI translation in learning translation from the perspective of cognitive linguistics. The study examines translation samples to enhance translation quality through a corpus-based approach. A parallel corpus of English - Vietnamese sentence pairs are constructed, covering such domains as business, media, and general language. The data are analyzed using two translation strategies: AI Translation (AIT) and Human Translation (HT), grounded in such key theoretical frameworks as the theory of conceptual metaphor (Kövecses, 2005; Lakoff & Johnson, 1999, 2008) and the theory of semantic frame (Fillmore (1976, 1982; Croft & Cruse, 2004). The features of cognitive linguistics are displayed that are not characteristic of AI Bots and present how language learners acquire cognitive translation of languages. The study aims to demonstrate that translation works with the assistance of theoretical frameworks will serve as a systematic decision-making framework that enhances semantic accuracy, fluency, and communicative effectiveness in different languages. The findings reveal a substantial improvement in translation quality when theoretical frameworks are applied, with the number of errors reduced. These findings display the importance of integrating cognitive theories into both translation teaching and translator training. This suggests the need for combining theoretical knowledge with technological tools in the evolving landscape of translation studies.