Enhancing VR Customer Service Training: A System for Generating Customer Queries and Evaluating Trainee Responses

Virtual customer service training using avatars eliminates the need for physical facilities, reducing costs and enabling remote participation. However, the challenge lies in the authoring cost of preparing service specific question and the necessity of experienced instructors. To address this, we employ LLM technology to generate service specific question and evaluate trainee's answer mitigating authoring costs. Despite LLMs having general knowledge limitations, we integrate RAG to imbue them with specific service knowledge. This innovation facilitates the generation of service specific questions. Furthermore, we are developing a self-training system where RAG assesses the correctness of trainee answers, enabling independent learning (without an instructor). This paper discusses the issues faced and insights gained during the development of our system.