Introducing Stimulus Information Generation using Scene Segmentation in the Group Discussion Support System AIR-VAS

Abstract

In today's rapidly progressing information age, the diversi cation of individual values has led to prominent social issues arising from value conicts. We address this challenge by developing AIR-VAS, a discussion support system designed to promote mutual understanding and synergy among groups with diverse values. The core function of AIR-VAS is to facilitate awareness of others' values during group discussions. It achieves this by recognizing and sharing other group's characteristic opinions, enabling participants to explore new perspectives and dimensions to the discussion topic. This paper introduces a method for discussion scene segmentation based on sentence vectors that capture textual semantics using neural language models. By integrating the mechanism of selecting stimulus information based on scene segmentation into the system, we enhance the effectiveness of awareness support. Our experimental results demonstrate how unique ideas selected based on sentence vector distances promote diverse idea generation, providing valuable insights into fostering synergy among individuals with differing values in group discussions.