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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 loose follow up to the course NPFL123
Dialogue Systems, but can be taken independently.
Last update: Vidová Hladká Barbora, doc. Mgr., Ph.D. (25.01.2019)
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Passing the final exam (written test based on the contents of lectures), finishing lab session homeworks (implementation of machine learning models for dialogue systems). Last update: Vidová Hladká Barbora, doc. Mgr., Ph.D. (13.05.2019)
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Last update: Dušek Ondřej, Mgr. et Mgr., Ph.D. (10.05.2022)
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Brief introduction into dialogue systems
Natural language understanding (NLU)
Dialogue management
Response generation (NLG)
End-to-end dialogue systems
Open-domain systems (chatbots)
Ethical issues in dialogue systems
Multimodal systems
Last update: Dušek Ondřej, Mgr. et Mgr., Ph.D. (23.05.2025)
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