Emotional Musical Prosody: Validated Vocal Dataset for Human Robot Interaction

TL;DR

This paper introduces a validated 4.2-hour emotional vocal dataset based on musical prosody, aimed at improving human-robot interaction by enhancing emotional expression and trust.

Contribution

It presents a new, extensively validated dataset of improvised emotional vocal phrases for use in robotic systems to better convey emotions.

Findings

Dataset is validated through listening tests.

Preliminary results show potential for generative systems.

Enhances emotional communication in human-robot interaction.

Abstract

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.