SIS code: 
Semester: 
winter
E-credits: 
5
Examination: 
C+Ex

This is the new version of the course for the '19/20 Fall semester.

Summary

This course will present 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.

Logistics

The course will be taught in English, but we're happy to explain in Czech as well.statistical dialogue system schema

Lectures: Thu 10:40 S1 (room changed!)
Labs: Thu 14:00 SW1
(labs will primarily take place online & in groups, with a few meetings during the semester)

Lectures

Slides from past lectures will appear here:

Labs

Lab assignments appear in the dedicated GitLab repository.

Topics to be covered

  • Brief introduction into dialogue systems
    • dialogue systems applications
    • basic components of dialogue systems
    • knowledge representation in dialogue systems
    • data and evaluation
  • Language understanding (SLU)
    • semantic representation of utterances
    • statistical methods for SLU
  • Dialogue management
    • dialogue representation as a (Partially Observable) Markov Decision Process
    • dialogue state tracking
    • action selection
    • reinforcement learning
    • user simulation
    • deep reinforcement learning (using neural networks)
  • Response generation (NLG)
    • introduction to NLG, basic methods (templates)
    • generation using neural networks
  • Open-domain systems (chatbots)
    • generative systems (sequence-to-sequence, hierarchical models)
    • information retrieval
    • ensemble systems
  • End-to-end dialogue systems
    • training based on dialogue logs in a limited domain
    • multi-task learning
  • Multi-domain systems
    • one-shot learning
  • Multimodal systems
    • visual dialogue

Recommended reading

  • McTear et al.: The Conversational Interface: Talking to Smart Devices. Springer 2016.
  • Psutka et al.: Mluvíme s počítačem česky. Academia 2006.
  • + current papers from the field