InnerSelf: Designing Self-Deepfaked Voice for Emotional Well-being

Fuente: arXiv
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Autores principales: Dai, Guang, Wang, Pinhao, Yao, Cheng, Ying, Fangtian
Formato: Preprint
Publicado: 2025
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author Dai, Guang
Wang, Pinhao
Yao, Cheng
Ying, Fangtian
author_facet Dai, Guang
Wang, Pinhao
Yao, Cheng
Ying, Fangtian
contents One's own voice is one of the most frequently heard voices. Studies found that hearing and talking to oneself have positive psychological effects. However, the design and implementation of self-voice for emotional regulation in HCI have yet to be explored. In this paper, we introduce InnerSelf, an innovative voice system based on speech synthesis technologies and the Large Language Model. It allows users to engage in supportive and empathic dialogue with their deepfake voice. By manipulating positive self-talk, our system aims to promote self-disclosure and regulation, reshaping negative thoughts and improving emotional well-being.
format Preprint
id arxiv_https___arxiv_org_abs_2503_14257
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle InnerSelf: Designing Self-Deepfaked Voice for Emotional Well-being
Dai, Guang
Wang, Pinhao
Yao, Cheng
Ying, Fangtian
Human-Computer Interaction
One's own voice is one of the most frequently heard voices. Studies found that hearing and talking to oneself have positive psychological effects. However, the design and implementation of self-voice for emotional regulation in HCI have yet to be explored. In this paper, we introduce InnerSelf, an innovative voice system based on speech synthesis technologies and the Large Language Model. It allows users to engage in supportive and empathic dialogue with their deepfake voice. By manipulating positive self-talk, our system aims to promote self-disclosure and regulation, reshaping negative thoughts and improving emotional well-being.
title InnerSelf: Designing Self-Deepfaked Voice for Emotional Well-being
topic Human-Computer Interaction
url https://arxiv.org/abs/2503.14257