Developing the Ability to Communicate for SemuBot, a Social Humanoid Robot
Name
Albert Unn
Abstract
Social robots have been developed for decades, but creating the ability to have natural conversations with humans without strict rules has been a significant challenge. Approaches for communication between humans and robots have relied on pre-programmed dialogue options, which limits interaction and forces users to follow strictly defined rules. The rapid advancement of large language models offers a promising solution to this problem, enabling significant progress to be made in the quality of social robots. SemuBot is a student project to develop the first Estonian-speaking social humanoid robot, and this work focuses on exploring various solutions to achieve its ability to have conversations with people using a large language model. The study explores the use of three key components: speech recognition, large language models, and speech synthesis. The goal is to find optimal solutions for these components in the context of social robotics. As a result, a hardware and software solution for the social humanoid robot SemuBot is developed, enabling the robot to engage in natural conversations with people in Estonian.
Graduation Thesis language
Estonian
Graduation Thesis type
Bachelor - Computer Science
Supervisor(s)
Karl Kruusamäe, Agnes Luhtaru, Hele-Andra Kuulmets
Defence year
2024