تقرير
Multipar-T: Multiparty-Transformer for Capturing Contingent Behaviors in Group Conversations
| العنوان: | Multipar-T: Multiparty-Transformer for Capturing Contingent Behaviors in Group Conversations |
|---|---|
| المؤلفون: | Lee, Dong Won, Kim, Yubin, Picard, Rosalind, Breazeal, Cynthia, Park, Hae Won |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning |
| الوصف: | As we move closer to real-world AI systems, AI agents must be able to deal with multiparty (group) conversations. Recognizing and interpreting multiparty behaviors is challenging, as the system must recognize individual behavioral cues, deal with the complexity of multiple streams of data from multiple people, and recognize the subtle contingent social exchanges that take place amongst group members. To tackle this challenge, we propose the Multiparty-Transformer (Multipar-T), a transformer model for multiparty behavior modeling. The core component of our proposed approach is the Crossperson Attention, which is specifically designed to detect contingent behavior between pairs of people. We verify the effectiveness of Multipar-T on a publicly available video-based group engagement detection benchmark, where it outperforms state-of-the-art approaches in average F-1 scores by 5.2% and individual class F-1 scores by up to 10.0%. Through qualitative analysis, we show that our Crossperson Attention module is able to discover contingent behavior. Comment: 7 pages, 4 figures, IJCAI |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2304.12204 |
| رقم الأكسشن: | edsarx.2304.12204 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |