Leveraging AI-Generated Emotional Self-Voice to Nudge People towards their Ideal Selves

TL;DR

This paper presents Emotional Self-Voice (ESV), a system that uses AI to generate personalized, emotionally expressive voices to help individuals visualize and move towards their ideal selves, showing promising results in a user study.

Contribution

It introduces ESV, combining language models and voice cloning to create personalized emotional voices for behavioral nudging, a novel approach in self-improvement technology.

Findings

ESV increased resilience, confidence, motivation, and goal commitment.

Participants found ESV more engaging and personalized than other methods.

The system shows potential as a personalized behavioral intervention.

Abstract

Emotions, shaped by past experiences, significantly influence decision-making and goal pursuit. Traditional cognitive-behavioral techniques for personal development rely on mental imagery to envision ideal selves, but may be less effective for individuals who struggle with visualization. This paper introduces Emotional Self-Voice (ESV), a novel system combining emotionally expressive language models and voice cloning technologies to render customized responses in the user's own voice. We investigate the potential of ESV to nudge individuals towards their ideal selves in a study with 60 participants. Across all three conditions (ESV, text-only, and mental imagination), we observed an increase in resilience, confidence, motivation, and goal commitment, and the ESV condition was perceived as uniquely engaging and personalized. We discuss the implications of designing generated self-voice systems as a personalized behavioral intervention for different scenarios.