BM1

Advanced Natural Language Processing

This class covers fundamental and advanced methods for natural language processing. The focus is on symbolic and statistical techniques for

  • language modeling
  • part-of-speech tagging
  • speech recognition and synthesis
  • parsing
  • machine translation
  • semantic processing
  • grammar induction
  • After completing the course successfully, you will be able to read and understand current conference and journal publications in computational linguistics. You will thus be well prepared to study advanced topics in the AM1x and PM1 modules.

    The class will be accompanied by regular programming assignments over the course of the semester, in which you will gain a deeper understanding of the course material. For the final exam, each student defines a small project in natural language processing and carries it out during the term break.

    module coordinator:

    Prof. Dr. Alexander Koller

    Course Materials:

    Program Overview