Human-Machine Dialogue
Master in Artificial Intelligence Systems
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Description
Computers, agents capable of engaging in meaningful conversations with humans, are becoming increasingly prevalent across various industries and applications. In this course, we delve into the fundamental principles of interaction and dialogue between humans and computers, as well as their underlying structure. We draw from conversation linguistics to develop computational dialogue models, dialogue system architectures, and their evaluation. The second part of the course equips students with methodologies for designing conversational agents, data-driven training (including generative AI models, agentic frameworks, and end-to-end pipelines), design tools, and a project-based lab that tackles real-world use cases. This approach ensures that students ground the concepts and learn how to apply them in real-life scenarios.
Students will design, develop, and evaluate human-machine dialogue systems for an application with large language models and/or agentic frameworks.
=======Lecture Topics, Slides, Lab============
Below are the topics that the course will cover.
The course is based on lectures, lab sessions, and project coaching.
The material is updated weekly throughout the semester.
Course Description (Incl. Assignments and Student Evaluation)
Basics of Human-Computer Interaction
Linguistics of Conversations
Conversational Design and Wireframing
Emotions in Dialogue
Dialogue Models
Dialogue Evaluation
Reinforcement Learning and Applications to HMD
Natural Language Generation
Large Language Models ( Lecture and Lab)
Crowdsourcing for Data Collection
Ethics and Conversational AI
LAB
Lab Workplan for the HMD project
Past project Reports : Spoken HMD with Alexa, Project with LLMs
