This is the new version of the course for the '20/21 Fall semester. You can have a look at last year's version for old slides and more information.
This course presents advanced problems and current state-of-the-art in the field of dialogue systems, voice assistants, and conversational systems (chatbots). After a brief introduction into the topic, the course will focus mainly on the application of machine learning – especially deep learning/neural networks – in the individual components of the traditional dialogue system architecture as well as in end-to-end approaches (joining multiple components together).
This course is a follow-up to the course NPFL123 Dialogue Systems, but can be taken independently – important basics will be repeated. All required deep learning concepts will be explained, but only briefly, so some machine learning background is recommended.
The course will be taught in English, but we're happy to explain in Czech as well.
The course will be taught online over Zoom, given the current pandemic. All lectures will be recorded so you can catch up later. Note that recordings of students' voices will not be retained to comply with privacy requirements – don't hesitate to talk in the lectures!
There is a shared Slack workspace for the course – email us to get access.
The schedule is the following:
Lectures + Labs: Tue 9:50-12:10
We start at 9:50 each week – the lab session is not taking place everytime, so sometimes we'll finish earlier.
Zoom meeting ID: 953 7826 3918
Password is the SIS code of this course (capitalized)
If you can't access Zoom, email us or text us on Slack.
To successfully finish this course, you'll need to:
Slides and from past lectures will appear here (video links are sent directly to students; email us if you want to get video links).
Lab assignments will appear in the dedicated GitLab repository. There's also videos for the lab instructions (email us to get links).