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

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.

References in corpus (3)

• MindfulDiary: Harnessing Large Language Model to Support Psychiatric Patients' Journaling
• An Overview of Affective Speech Synthesis and Conversion in the Deep Learning Era
• Contextual AI Journaling: Integrating LLM and Time Series Behavioral Sensing Technology to Promote Self-Reflection and Well-being using the MindScape App

Cited by in corpus (2)

• Restoration, Exploration and Transformation: How Youth Engage Character.AI Chatbots for Feels, Fun and Finding themselves
• Toward Natural and Companionable Virtual Agents via Cross-Temporal Emotional Modeling