[3R1-OS-13b] OS-13

[3R1-OS-13b-04] Utterance Classification in Motivational Interviewing using Verbal, Facial, and Speech information

Tomoya Tanaka¹, Tatsuya Sakato², 〇Yukiko Nakano² (1. Graduate School of Science and Technology, Seikei University, 2. Seikei University Faculty of Science and Technology)

Keywords:Motivational Interviewing, Multimodal Interaction, Classification

Motivational interviewing (MI) is a counseling technique that aims to elicit clients' reasons for behavior change. In MI, a coding scheme called Motivational Interviewing Skill Code (MISC) has been established. In this study, we first annotated counselor utterances in a Japanese MI corpus using MISC coding scheme, and merged the labels into 13 categories. Then, we created 13-class classification models using two approaches. The first approach is to create classification models by fine-tuning a large-scale language model (LLM). The second approach is to create cross-modal transformer models based on BERT. Experimental results showed that the best F1-score was 0.83 for complex reflection category, which includes summaries and metaphors. We also discussed the impact of unbalanced data.