AI Voice Cloning Technology under Human-machine Attachment Shared Mechanism Behavior Research

AI voice cloning technology, with its unique anthropomorphic and authenticity characteristics, successfully replicates human voice and endows it with eternal value, thus spawning a new mode of human-machine attachment. Based on the SOR model, this study introduces key variables to reconstruct the voice sharing model and uses structural equation modeling (SEM) to conduct a deep analysis of 302 questionnaire data. The research results show that the anthropomorphism and authenticity of technology, as well as users' attachment emotions, have significant positive effects on sharing behavior, while trust attitude shows a negative effect. In addition, attachment and trust play intermediary roles in sharing behavior. Based on these findings, this paper proposes suggestions for eliminating barriers, building trust, and returning to the user as the main subject to restart the human-machine attachment relationship, providing a new perspective for the research on the mechanism of voice sharing behavior under the background of human-machine attachment, aiming to build a closer and more stable human-machine voice symbiotic relationship.

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Publication Details

Journal
Communications in Humanities Research
Published
2024-10-18
DOI
https://doi.org/10.54254/2753-7064/36/2024bj1006
Primary Topic
Regional Development and Environment
Type
article
Field-Weighted Citation Impact
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article

AI Voice Cloning Technology under Human-machine Attachment Shared Mechanism Behavior Research

Kai Meng
Communications in Humanities Research
Regional Development and Environment
article

AI Voice Cloning Technology under Human-machine Attachment Shared Mechanism Behavior Research

Kai Meng
article en

Abstract

AI voice cloning technology, with its unique anthropomorphic and authenticity characteristics, successfully replicates human voice and endows it with eternal value, thus spawning a new mode of human-machine attachment. Based on the SOR model, this study introduces key variables to reconstruct the voice sharing model and uses structural equation modeling (SEM) to conduct a deep analysis of 302 questionnaire data. The research results show that the anthropomorphism and authenticity of technology, as well as users' attachment emotions, have significant positive effects on sharing behavior, while trust attitude shows a negative effect. In addition, attachment and trust play intermediary roles in sharing behavior. Based on these findings, this paper proposes suggestions for eliminating barriers, building trust, and returning to the user as the main subject to restart the human-machine attachment relationship, providing a new perspective for the research on the mechanism of voice sharing behavior under the background of human-machine attachment, aiming to build a closer and more stable human-machine voice symbiotic relationship.

Communications in Humanities ResearchVol. 36(1)
Beijing Normal University (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 71%
Regional Development and Environment
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