Human-Machine Dialogue

Master in Artificial Intelligence Systems

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Robots that can talk or chat with humans are becoming pervasive in many industry and consumer domains. Artificial Intelligent Systems (AIS) using natural language can interact with humans and operate in command-and-control, information retrieval, or cooperative decision-support tasks. In this course, we review the basic principles of human-computer interaction and then address the fundamental structures of human conversations. We derive the concepts from conversation linguistics discourse analysis to describe computational dialogue models, dialogue system architectures, and their evaluation. In the second part of the course, we provide methodologies for the design of conversational agents, data-driven training, design tools, and a project-based lab addressing real use cases.

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=======Lecture Topics, Slides, Lab============

Below are the topics that the course will cover. The course is project-based, meaning
that the student's requirement is to design, train, and develop a human-machine dialogue system by
the end of the course, whether the "touch point" is a smartphone, desktop web browser, a smart speaker,
a smartwatch, in-car "invisible" interface. The course is based on lecture and lab sessions.

Course Description (Incl. Assignments and Student Evaluation)
Basics of Human-Computer Interaction
Conversational Design and Wireframing (
1, 2 )
Linguistics of Conversations
Emotions in Dialogue
Dialogue Models
Natural Language Generation
Machine Learning Models for Conversational Models ( Lab )
Large Language Models and Applications ( Lab )
Dialogue Evaluation
Reinforcement Learning for HMD
Privacy for Data Collection
Crowdsourcing for Data Collection
Ethics and Privacy for Human-Machine Dialogue Systems
Tools and frameworks for Data Generation and HMD Development (Labs )
Project Presentation and Guidelines
Project Report Template (from a top grade student)
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