Digital Speech Makeup: Voice Conversion Based Altered Auditory Feedback for Transforming Self-Representation

Abstract

Makeup (i.e., cosmetics) has long been used to transform not only one's appearance but also their self-representation. Previous studies have demonstrated that visual transformations can induce a variety of effects on self-representation. Herein, we introduce Digital Speech Makeup (DSM), the novel concept of using voice conversion (VC) based auditory feedback to transform human self-representation. We implemented a proof-of-concept system that leverages a state-of-the-art algorithm for near real-time VC and bone-conduction headphones for resolving speech disruptions caused by delayed auditory feedback. Our user study confirmed that conversing for a few dozen minutes using the system influenced participants' speech ownership and implicit bias. Furthermore, we reviewed the participants' comments about the experience of DSM and gained additional qualitative insight into possible future directions for the concept. Our work represents the first step towards utilizing VC to design various interpersonal interactions, centered on influencing the users' psychological state.