Introduction Human Language Technology


Course Objective

Students learn to critically reflect on one of the big debates in our
time: can machines really understand us and how can we communicate with
machines that see the world differently? They also get an introduction
into Natural Language Processing and gain their first practical
experience in building a first rule-based system, and building a
classifier for text analysis through machine learning. Finally, we
introduce to our students our major research projects on the themes of
identity, reference and perspectives.

Course Content

Did you ever wonder how to communicate with a robot in your own
language? In this course you learn what it takes and meet our own robot
that students programmed.
The aim of this course is to give an introduction to the Human Language
Technology track of the (Research) Master Linguistics. We place the
modelling of the human language capacity within the broader perspective
of behavioural, empirical and euro-cognitive science. How does
understanding of language work? How do recent theories about embodiment
of meaning in language relate to recent developments in Deep Learning
such as distributional semantics and neural networks? Language is
natural to people but not to machines. We take the perspective of a
machine that needs to understand and generate language to communicate
with people. The machine can be a robot, a chatbot or a reading machine.
We will look into the big AI debate in relation to language,
communication and intelligence, started by Alan Turing and John Searle:
how to convince your self-driving car to make a u-turn! Guess what, we
will introduce you to our robots to experience how difficult it is to
communicate with them.

Teaching Methods

The course consists of a theoretical class and a practical class. During
the theoretical class, we discuss selection of papers and we have a
debate about the theoretical concepts and implications. During the
practical class, the students apply Natural Language Processing to text
and analyse these in relation to the theoretical aspects discussed
before. Students need a laptop to perform the practical classes.

Method of Assessment

There is a practical assignment every week. Students need to complete
all the assignments. Personal feedback is provided but the assignments
are not further graded. The course is graded through a final essay on
the topic “Can machine understand human language”.

Target Audience

This course is targeting students with a linguistics or a computer
science (AI) background.

General Information

Course Code L_AAMPALG016
Credits 6 EC
Period P1
Course Level 500
Language of Tuition English
Faculty Faculty of Humanities
Course Coordinator prof. dr. P.T.J.M. Vossen
Examiner prof. dr. P.T.J.M. Vossen
Teaching Staff prof. dr. P.T.J.M. Vossen

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Seminar