Affective gesturing with music mood recognition

Abstract

The recognition of emotions and the generation of appropriate responses is a key component for facilitating more natural human-robot interaction. Music, often called the “language of emotions,” is a particularly useful medium for investigating questions involving the expression of emotion. Likewise, movements and gestures, such as dance, can also communicate specific emotions to human observers. We apply an efficient, causal technique for estimating the emotions (mood) from music audio to enable a humanoid to perform gestures reflecting the musical mood. We implement this system using Hubo, an adult-sized humanoid that has been used in several applications of musical robotics. Our preliminary experiments indicate that the system is able to produce dance-like gestures that are judged by human observers to match the perceived emotion of the music.