Advancements and challenges in AI-driven creative translation: A comprehensive analysis

Abstract

Abstract. This article provides an in-depth exploration of the use of artificial intelligence (AI) in creative translation, highlighting the advancements in machine learning algorithms and the challenges of cultural and emotional congruence. It examines several key aspects: the efficacy of sequence-to-sequence and transformer models in enhancing translation accuracy, the role of AI in cultural contextualization, and the integration of emotional intelligence to handle subtleties in translations. Comparative case studies illustrate AI's performance against human translators in handling culturally dense texts, while adaptive algorithms demonstrate the customization of AI systems for specific cultural contexts. Furthermore, the article delves into the quantitative methods used to evaluate AI translation accuracy, such as BLEU and METEOR scores, and discusses innovative techniques for improving AI translation quality through reinforced learning and context-aware translations. The potential future directions of AI in creative translation, including the use of augmented reality and large-scale language models, are also discussed, presenting a vision of AI's evolving role in breaking linguistic and cultural barriers.