Machine Translation

This book provides an in-depth discussion of the evolution of machine translation from rule-based systems to advanced deep learning models and Large Language Models (LLMs). Ideal for researchers, practitioners, and students in NLP and AI, this book bridges theoretical foundations with real-world applications. This comprehensive guide covers traditional approaches, statistical machine translation (SMT) and the transformative impact of neural networks and transformers. It explores the practical applications of large language models (LLMs) like GPT, addressing evaluation metrics and ongoing research challenges. Ideal for researchers, practitioners and students in natural language processing (NLP) and artificial intelligence (AI), Machine Translation bridges theoretical foundations with real-world applications, offering valuable insights into the future of machine translation technology to understand the full spectrum of machine translation advancements, from foundational theories to the latest generative AI technologies.