Feature Design for Dialogue Stage Prediction in Narrative Therapy

Abstract

Research on dialogue agents that reproduce counseling dialogues by psychotherapy is in progress. However, dialogue agents currently do not have the same psychotherapy technology as same as psychotherapists. Because of that, the dialogue control of dialogue agents depends on the prepared scenario. We aim to realize a counseling dialogue system that can promote flexible dialogue for problem-solving by introducing the dialogue stage prediction to the dialogue system. Therefore, as the first step, we designed the features suitable for predicting the progress stage of the dialogue. As a result of conducting a dialogue stage division experiment by non-hierarchical clustering using those features designed for dialogue stage prediction, the feature considering the context information and polarity during the dialogue showed the best performance with Purity 0.69, Inverse Purity 0.72, and F value 0.70. Therefore, the effectiveness of our proposed feature design is confirmed.