What if HAL breathed? Enhancing Empathy in Human-AI Interactions with Breathing Speech Synthesis

Abstract

AI Agents increasingly leverage speech synthesis models to communicate with their users. This study explores the integration of breathing patterns into synthesized speech to deepen empathy towards AI agents. The research methodologically diverges from traditional empathy studies and speech evaluation standards by proposing to the participants the resolution of an emotional dilemma within a cooperative game scenario, where they face a choice reflecting their empathetic engagement with an AI partner. The introduction of a novel speech assessment method that takes into account the interactive and contextual aspects of conversational speech is the first novelty of the paper. The second novelty is in the findings which indicate that breathing in synthesized speech significantly enhances agents' perceived naturalness and users' empathy towards them.