Computational Linguistics Resources

1. Jurafsky, D., & Martin, J. H. (2024). Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition (3rd ed. draft). Stanford University. This is the biggest and most complete textbook in the field. It explains everything from basic word counting and grammar rules to how modern AI (like ChatGPT) is built. You can read this when you want to deeply understand the theory and the mathematical formulas computers use to understand human language. 2. Bird, S., Klein, E., & Loper, E. (2009). Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit. O'Reilly Media. This book is like a practical coding class. Instead of dry theory, it teaches you how to use the Python programming language to build small language tools. You will learn to write code that automatically finds nouns, verbs, or draws grammar trees. 3. McEnery, T., & Hardie, A. (2011). Corpus Linguistics: Method, Theory and Practice. Cambridge University Press. This book does not teach programming. It completely focuses on building and using a "Corpus" (a huge language database). It guides you on how to collect millions of emails, articles, or messages, and then use software to discover how people actually use words in real-life communication.