Machine Translation Model

Machine translation models aim to automatically translate text between different languages, striving for accuracy and fluency comparable to human translation. Current research focuses on improving translation quality for low-resource languages, handling the nuances of conversational and literary text, and developing more robust evaluation metrics, often leveraging large language models (LLMs) and transformer architectures like mBART and mT5. These advancements have significant implications for global communication, cross-cultural understanding, and access to information, particularly in underserved communities.