  Human collaboration with robotics is dependant on the development of a
relationship between human and robot, without which performance and utilization
can decrease. Emotion and personality conveyance has been shown to enhance
robotic collaborations, with improved human-robot relationships and increased
trust. One under-explored way for an artificial agent to convey emotions is
through non-linguistic musical prosody. In this work we present a new 4.2 hour
dataset of improvised emotional vocal phrases based on the Geneva Emotion
Wheel. This dataset has been validated through extensive listening tests and
shows promising preliminary results for use in generative systems.
