MC5 Introduction to Natural Language Processing


Natural Language Processing has become one of the most important disciplines for information processing in the digital age. It is a broad field covering technologies as diverse as machine translation, information retrieval, sentiment analysis, chat bots or automatic speech recognition. And it brings together ideas and methods from areas as diverse as linguistics, artificial intelligence, logic, machine learning, a.o. In this class, I will start with an introduction into basic challenges and notions of speech and language processing, and then focus on a core question in NLP: how do we design machines that are able to understand what a sentence means and able to produce sentences that convey meaning?

Session 1: Basics of text and speech processing (automatic speech recognition, tokenization, part-of-speech tagging, morphology, parsing, generation etc.)
Session 2: Modeling the meaning of sentences and texts
Session 3: Modeling the meaning of words
Session 4: Hot topics in computational semantics (grounding, conversation modeling, multi-modality)


Familiarize the audience with different methods and paradigms in NLP in general, and computational semantics in particular.


THE classic intro to NLP:
Dan Jurafsky and James H. Martin: Speech and Language Processing

Course location


Course requirements


Instructor information.

Sina Zarrieß


Bielefeld University


Sina Zarrieß is a temporary Professor for Theoretical Computational Linguistics in Bielefeld, where she also did a PostDoc at the Excellence Center on Cognitive Interaction Technology (CITEC) . She did her PhD at the Institute of Natural Language Processing (IMS) in Stuttgart. Before that, she studied Computational Linguistics and Romance Philology in Potsdam and Toulouse. Her research focusses on natural language generation, dialogue, computational semantics, and grounding.