Taro Asada

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About

Taro Asada is a pioneering researcher in affective computing and human-robot interaction, with a focused mission to create robots that can genuinely understand and respond to human emotions. His work centers on developing intelligent systems for emotion recognition, particularly through the analysis of vocalizations and facial expressions. Asada’s most impactful contribution is his 2013 paper on recognizing a baby’s emotional cry, which has garnered 21 citations. In this work, he developed a pattern recognition method using 32-dimensional Fast Fourier Transform to classify infant cries as discomfort, hunger, or sleepiness—a critical step toward creating empathetic robotic baby caregivers. He further advanced the field with a 2015 study on facial expression recognition using thermal imaging, analyzing temperature changes in the mouth and jaw area with two-dimensional discrete cosine transforms. His 2011 research on vowel judgment for facial expression recognition also contributes to the goal of enabling robots to perceive human mental states. Through these innovations, Asada is laying the groundwork for socially assistive robots that can provide more natural, caring interactions in healthcare and domestic settings.