Natural Language Processing (NLP) is a field of study within artificial intelligence that focuses on enabling computers to understand, interpret, and generate human language. It bridges the gap between human communication and computer comprehension, allowing machines to process and analyze large amounts of text or speech data.
Key research areas within NLP include language modeling, text classification, sentiment analysis, machine translation, question answering, and speech recognition. NLP systems are built using algorithms and models like neural networks, transformers, and deep learning architectures, which allow them to recognize patterns in language, understand context, and even generate coherent responses.
Applications of NLP are widespread, powering technologies such as chatbots, virtual assistants, language translation services, and automatic summarization tools. The field is rapidly advancing with innovations in understanding nuances like emotion, sarcasm, and multilingual processing, making interactions between humans and machines more natural and intuitive.
Faculty
Chris Callison-Burch
Sharath Guntuku
Mark Liberman
Dan Roth
Lyle Ungar
Charles Yang
