Auditory mood detection for social and educational robots

— Social robots face the fundamental challenge of detecting and adapting their behavior to the current social mood. For example, robots that assist teachers in early education must choose different behaviors depending on whether the children are crying, laughing, sleeping, or singing songs. Interactive robotic applications require perceptual algorithms that both run in real time and are adaptable to the challenging conditions of daily life. This paper explores a novel approach to auditory mood detection which was born out of our experience immersing social robots in classroom environments. We propose a new set of low-level spectral contrast features that extends a class of features which have proven very successful for object recognition in the modern computer vision literature. Features are selected and combined using machine learning approaches so as to make decisions about the ongoing auditory mood. We demonstrate excellent performance on two standard emotional speech databases (t...

• Type: Conference
• Year: 2008
• Where: ICRA
• Authors: Paul Ruvolo, Ian R. Fasel, Javier R. Movellan
• Keywords: Auditory Mood, Current Social Mood, ICRA 2008, Robotics, Social Robots