Self context-aware emotion perception on human-robot interaction
CoRR(2024)
摘要
Emotion recognition plays a crucial role in various domains of human-robot
interaction. In long-term interactions with humans, robots need to respond
continuously and accurately, however, the mainstream emotion recognition
methods mostly focus on short-term emotion recognition, disregarding the
context in which emotions are perceived. Humans consider that contextual
information and different contexts can lead to completely different emotional
expressions. In this paper, we introduce self context-aware model (SCAM) that
employs a two-dimensional emotion coordinate system for anchoring and
re-labeling distinct emotions. Simultaneously, it incorporates its distinctive
information retention structure and contextual loss. This approach has yielded
significant improvements across audio, video, and multimodal. In the auditory
modality, there has been a notable enhancement in accuracy, rising from 63.10
to 72.46
increasing from 77.03
an elevation from 77.48
reliability and usability of SCAM on robots through psychology experiments.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要