Empowering Multilingual AI: Cross-Lingual Transfer Learning

Abstract

Multilingual Natural Language Processing (NLP) and Cross-Lingual Transfer Learning have emerged as pivotal fields in the realm of language technology. This abstract explores the essential concepts and methodologies behind these areas, shedding light on their significance in a world characterized by linguistic diversity. Multilingual NLP enables machines to process global collaboration. Cross-lingual transfer learning, on the other hand, leverages knowledge from one language to enhance NLP tasks in another, facilitating efficient resource utilization and improved model performance. The abstract highlights the growing relevance of these approaches in a multilingual and interconnected world, underscoring their potential to reshape the future of natural language understanding and communication.