本研究探討創作者身份標籤（人類與AI）對音樂評價的影響，隨著生成式AI在音樂創作中的應用日增，大眾對其情感表達與創作能力仍抱持質疑，可能導致相同作品因標示不同而評價有別。透過實驗問卷將受試者隨機分派至八組，分為僅聽單一創作者音樂與同時聽AI與人類創作的組別，比較情感、偏好與技術層面的評價差異，並探討曲風（抒情與舞曲）是否調節此效應。結果顯示，AI音樂在三層面皆低於人類作品，且在混合創作者組中，抒情曲風下身份標籤的影響更為顯著。本研究揭示聽眾對AI音樂的潛在偏見，並強調創作者標示在實驗設計中的關鍵角色，對未來AI音樂接受度與設計應用具重要參考價值。

This study examines the impact of creator identity labels (human vs. AI) on music evaluation. As generative AI becomes increasingly prevalent in music creation, public skepticism toward its emotional expressiveness and creative capacity may lead to biased judgments based solely on authorship attribution. Using an experimental questionnaire, participants were randomly as-signed to one of eight groups, either exposed to music from a single creator type or both AI- and human-labeled pieces. Evaluations were compared across emotional, preference, and technical dimensions, and genre (lyrical vs. dance) was tested as a moderator. Results showed that AI-generated music received lower ratings across all dimensions, with more pronounced differ-ences in lyrical genres within the mixed-creator condition. These findings highlight audience bias against AI-generated music and underscore the importance of authorship information in ex-perimental design, offering valuable insights into the acceptance and application of AI in creative industries.

〔1〕A. M. Bel, “Emotional valence and vividness of imagery predict aesthetic appeal in
music,” Psychomusicology: Music, Mind, and Brain, vol. 29, no. 2–3, December 2019, pp. 128–135.
〔2〕A. S. Jago, “Algorithms and authenticity,” Academy of Management Discoveries,Vol. 5, No. 1, 2019, Mar., pp. 5–31.
〔3〕B. Biedermann, H. Strauß, and M. Zentner, “Different Genres, Different Emotions?An Analysis of the Influence of Individual Preferences and Genre on Musically
Evoked Emotions,” Proc. Int. Conv. Psychol. Sci. (ICPS), 2019.
〔4〕C. Herremans, A. Chuan, and G. Chew, “A functional taxonomy of music generation systems,” ACM Computing Surveys, vol. 50, no. 5, 2017, pp. 69:1–69:30.
〔5〕C. Nass and B. Reeves, “Machines and mindlessness: Social responses to computers,”Journal of Social Issues, vol. 56, no. 1, 1996, pp. 81-103.
〔6〕C.-Y. Chiu, C. S. Dweck, J. Y. Tong, and H.-Y. Fu, “Lay theories of personality:Cornerstones of meaning in social cognition,”Journal of Personality and SocialPsychology, vol. 73, no. 1, 1997, pp. 19-30.
〔7〕D. B. Shank, C. Stefanik, C. Stuhlsatz, K. Kacirek, and A. M. Belfi, “AI composer bias:Listeners like music less when they think it was composed by an AI,” Journal of
Experimental Psychology: Applied, vol. 29, no. 3, Jan. 2022, pp. 676-692.
〔8〕E. T. Eerola, “Are the Emotions Expressed in Music Genre-specific? An Audio-based Evaluation of Datasets Spanning Classical, Film, Pop and Mixed Genres,” Journal of New Music Research, vol. 40, no. 4, 2011, pp. 349–366.30
〔9〕E. Waytz, J. Heafner, and B. Epley, “The mind in the machine: Anthropomorphism increases trust in an autonomous vehicle,” Journal of Experimental Social Psychology,vol. 52, 2014, pp. 113-117.
〔10〕H. Gangadharbatla, “The role of AI attribution knowledge in the evaluation ofartwork,” Empirical Studies of the Arts, vol. 40, no. 2, 2022, pp. 125–142.
〔11〕H. Zhu, Q. Liu, N. J. Yuan, C. Qin, J. Li, K. Zhang, G. Zhou, F. Wei, Y. Xu, and E.Chen, “XiaoIce Band: A melody and arrangement generation framework for pop music,” in Proc. ACM SIGKDD Int. Conf. Knowledge Discovery & Data Mining(KDD), London, UK, 2018,pp. 2837–2846.
〔12〕L. Bellaiche, U. Hess, and F. W. Mast, “Humans versus AI: Whether and why we prefer human-created compared to AI-created artwork,”Cognitive Research:Principles and Implications, vol. 8, no. 1, 2023, p. 31.
〔13〕Liu, Q. Tang, X. Zhao, H. Lu, G. Yuan, G. Wang, and G. Liu, “Neural activation of different music styles during emotion-evoking,”Psychology of Music, Vol. 49, No. 6,
November 2021, pp. 1546-1560.
〔14〕M. Zentner, D. Grandjean, and K. R. Scherer, “Emotions Evoked by the Sound of Music: Characterization, Classification, and Measurement.” Emotion, Vol 8, December
2008, pp. 494-521.
〔15〕M. Zissman and E. Neimark, “The influence of familiarity on evaluations of liking and goodness of several types of music,” The Journal of Psychology, vol. 124, no. 4, 1990,
pp. 401–412.
〔16〕P. N. Juslin and D. Västfjäll, “Emotional responses to music: The need to consider underlying mechanisms,” Behavioral and Brain Sciences, vol. 31, no. 5, 2008, pp. 559–575.31
〔17〕S. M. Broniarczyk and J. W. Alba, “The importance of the brand in brand extension,”Journal of Marketing Research, vol. 31, no. 2, 1994, pp. 214-228.
〔18〕ZENTNER, Marcel; GRANDJEAN, Didier; SCHERER, Klaus R. Emotions evoked by the sound of music: characterization, classification, and measurement. Emotion,2008, 8.4: 494.32