Meng-Ju Han

National Yang Ming Chiao Tung University

Papers

Total Citations

H-Index

About

Meng-Ju Han is a pioneering researcher in human-robot interaction (HRI), with a core focus on emotion recognition through multimodal sensory integration. Her work bridges computer vision and speech processing to enable robots to perceive and respond to human emotional states, a critical step toward more natural and empathetic machine interactions. In her most cited paper, "A New Information Fusion Method for Bimodal Robotic Emotion Recognition" (2008, 29 citations), Han introduced a novel approach that combines image and speech signals, significantly improving recognition accuracy over unimodal systems. She further advanced this field with "Speech signal-based emotion recognition and its application to entertainment robots" (2012, 17 citations), demonstrating how voice analysis can enhance robotic responsiveness in playful, real-world contexts. Her research also includes "Online learning design of an image-based facial expression recognition system" (2010, 10 citations), which explored adaptive learning techniques for dynamic environments. With over 56 cumulative citations, Han’s contributions have laid foundational groundwork for affective computing and socially intelligent robotics. Her work is especially notable for its practical orientation, targeting entertainment and service robots that require real-time, robust emotional understanding.