Leveraging AI-Generated Emotional Self-Voice to Nudge People towards their Ideal Selves
September 17, 2024 Β· Declared Dead Β· π International Conference on Human Factors in Computing Systems
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Authors
Cathy Mengying Fang, Phoebe Chua, Samantha Chan, Joanne Leong, Andria Bao, Pattie Maes
arXiv ID
2409.11531
Category
cs.HC: Human-Computer Interaction
Citations
9
Venue
International Conference on Human Factors in Computing Systems
Last Checked
4 months ago
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.
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