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Course, academic year 2023/2024
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Dialogue Systems - NPFL123
Title: Dialogové systémy
Guaranteed by: Institute of Formal and Applied Linguistics (32-UFAL)
Faculty: Faculty of Mathematics and Physics
Actual: from 2021
Semester: summer
E-Credits: 5
Hours per week, examination: summer s.:2/2, C+Ex [HT]
Capacity: unlimited
Min. number of students: unlimited
Virtual mobility / capacity: no
State of the course: taught
Language: English, Czech
Teaching methods: full-time
Teaching methods: full-time
Additional information:
Guarantor: Mgr. et Mgr. Ondřej Dušek, Ph.D.
Annotation -
Last update: doc. Mgr. Barbora Vidová Hladká, Ph.D. (25.04.2019)
This course is a detailed introduction into the architecture of spoken dialogue systems, voice assistants and conversational systems (chatbots). We will introduce the main components of dialogue systems (speech recognition, language understanding, dialogue management, language generation and speech synthesis) and show alternative approaches to their implementation. The lab sessions will be dedicated to implementing a simple dialogue system or a selected component.
Aim of the course -
Last update: doc. Mgr. Barbora Vidová Hladká, Ph.D. (25.04.2019)

The course aims to give a general overview of dialogue systems and explain the basic principles of their inner workings.

Course completion requirements -
Last update: Mgr. et Mgr. Ondřej Dušek, Ph.D. (06.05.2019)

Passing the final exam (written test based on the contents of lectures), finishing lab session homeworks (implementation tasks from the field of dialogue systems).

Literature -
Last update: Mgr. et Mgr. Ondřej Dušek, Ph.D. (10.05.2022)

Basic: Jurafsky & Martin: Speech & Language processing. 3rd ed. draft (chapter 23-26, especially 24).

Further reading:

McTear: Conversational AI: Dialogue Systems, Conversational Agents, and Chatbots. Morgan & Claypool 2021.

Jokinen & McTear: Spoken dialogue systems. Morgan & Claypool 2010.

Rieser & Lemon: Reinforcement learning for adaptive dialogue systems. Springer 2011.

McTear: Spoken Dialogue Technology. Springer 2004.

McTear et al.: The Conversational Interface: Talking to Smart Devices. Springer 2016.

Gao et al.: Neural Approaches to Conversational AI: Question Answering, Task-oriented Dialogues and Social Chatbots. now publishers 2019. (arXiv:1809.08267)

Syllabus -
Last update: Mgr. et Mgr. Ondřej Dušek, Ph.D. (10.05.2022)

1. Dialogue systems and artificial intelligence: introduction

  • dialogue system types (open/closed-domain, task/non-task oriented)
  • dialogue systems application
  • basic dialogue system components (text-to-text, speech-to-speech)
  • knowledge representation in dialogue systems
  • chatbots, AIML

2. Linguistic basics for dialogue processing

  • turn-taking, speech acts
  • conversational implicatures
  • grounding
  • coreference, anaphora, deixis

3. Data for dialogue systems, dialogue system evaluation

  • closed domain: Wizard-of-Oz
  • open domain: data sources, problems (cleanliness, risks of learning from users)
  • dialogue success rate
  • problems of chatbot evaluation

4. Language understanding

  • Sentence classification
  • named entity recognition

5. Dialogue state tracking

  • dialogue representation as an MDP or a POMDP

6. Dialogue management

  • reinforcement learning

7. Language generation

  • templates, rules
  • statistical generation, neural generative models

8. Question answering and voice assistants

  • Alexa, Google, Siri etc.
  • Knowledge bases, knowledge graph

9. Dialogue toolkits

  • intents, slots, entities
  • Alexa Skills, Google DialogFlow, IBM Watson Assistant

10. Speech recognition

  • speech signal processing
  • basic recognition approaches

11. Speech synthesis

  • phonetics/acoustics: sounds/phonemes, formants
  • speech synthesis methods

12. Chatbots (open-domain dialogue, chitchat)

  • rule-based chatbots
  • information retrieval
  • generative models
  • Hybrid systems (Alexa Prize)

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