Suhtlusvõimekuse arendamine sotsiaalsele humanoidrobotile SemuBot

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.