Serendipity Wall: A Discussion Support System Using Real-time Speech Recognition and Large Language Model.

Group discussions are important for exploring new ideas. One method to support discussions is presenting relevant keywords or images. However, the context of the conversation and information tended not to be taken into account. Therefore, we propose a system that develops group discussions by presenting related information in response to discussions. As a specific example, this study addressed academic discussions among HCI researchers. During brainstorming sessions, the system continuously transcribes the dialogue and generates embedding vectors of the discussions. These vectors are matched against those of existing research articles to identify relevant studies. Then, the system presented relevant studies on the large display with summarizing by an LLM. In a case study, this system had the effect of broadening the topics of discussion and facilitating the acquisition of new knowledge. A larger display area is desirable in terms of information volume and size. Therefore, in addition to large displays, virtual reality environments with headsets could be suitable for this system.