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Course, academic year 2018/2019
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Dialogue systems - NPFL123
Title in English: Dialogové systémy
Guaranteed by: Institute of Formal and Applied Linguistics (32-UFAL)
Faculty: Faculty of Mathematics and Physics
Actual: from 2018 to 2018
Semester: summer
E-Credits: 5
Hours per week, examination: summer s.:2/2 C+Ex [hours/week]
Capacity: unlimited
Min. number of students: unlimited
State of the course: taught
Language: Czech, English
Teaching methods: full-time
Guarantor: Mgr. et Mgr. Ondřej Dušek, Ph.D.
Aim of the course -
Last update: 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.

Course completion requirements -
Last update: Mgr. et Mgr. Ondřej Dušek, Ph.D. (10.06.2019)

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. (06.05.2019)

Basic: Jurafsky & Martin: Speech & Language processing. 3rd ed. draft (chapter 29-30). https://web.stanford.edu/~jurafsky/slp3/

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

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

McTear: Spoken Dialogue Technology. Springer 2004.

Syllabus -
Last update: Mgr. et Mgr. Ondřej Dušek, Ph.D. (06.05.2019)

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. Sentence classification

  • language understanding, dialogue state tracking

3. Named entity recognition, coreference resolution

4. Dialogue systems - dialogue management

5. Speech processing introduction

  • phonetics/acoustics: sounds, formants, speech signal processing

6. Speech recognition and synthesis

7. Statistical dialogue systems

  • dialogue representation as an MDP or a POMDP
  • using reinforcement learning

8. Language generation

  • templates, rules
  • statistical generation

9. Question answering and voice assistants

  • Siri, Google Home, Alexa
  • Knowledge base / knowledge graph

10. dialogue systems API

  • Facebook Messenger bots, LUIS, api.ai / Dialogflow

11. Chatbots (open-domain dialog)

  • AIML
  • Information retrieval (Cleverbot)
  • Statistical generation (seq2seq)
  • Hybrid systems (Alexa Prize)

12. Data for dialogue systems

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

13. Dialogue systems evaluation

  • dialogue success rate
  • problems of chatbot evaluation

 
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