人工智能生成音乐的感知——作曲者身份、个性特征、音乐偏好和感知人性的角色
Perception of AI-Generated Music -- The Role of Composer Identity, Personality Traits, Music Preferences, and Perceived Humanness
AI总结：
本研究探讨了人工智能生成音乐的感知因素，发现对人工智能的态度是影响听众喜爱和情感反应的主要因素，同时揭示了伦理、文化等在评价中的重要作用。
摘要：
人工智能生成艺术的迅速发展引发了关于观众如何感知和评价此类作品潜在偏见的讨论。本研究探讨了作曲信息和听众特征如何影响对人工智能生成音乐的感知，采用混合方法方法。利用来自两个AI音乐模型的多种风格的多样化刺激，我们检验了感知作者身份对喜爱和情感反应的影响，并探索了对人工智能的态度、个性特征和音乐相关变量如何影响评价。我们进一步评估了感知人性的影响，并分析开放式回答以揭示听众评判人工智能生成音乐的标准。对人工智能的态度被证明是预测人工智能生成音乐喜爱和情感强度的最佳预测因素。这一定量发现得到了我们主题分析的定性主题的补充，后者识别出伦理、文化和情境因素是听众评价人工智能生成音乐的重要标准。我们的结果提供了人们对人工智能工具生成音乐体验的细致视角，并指出了未来音乐感知研究中人类-人工智能互动中的关键因素和方法论考虑。
英文摘要：
The rapid rise of AI-generated art has sparked debate about potential biases in how audiences perceive and evaluate such works. This study investigates how composer information and listener characteristics shape the perception of AI-generated music, adopting a mixed-method approach. Using a diverse set of stimuli across various genres from two AI music models, we examine effects of perceived authorship on liking and emotional responses, and explore how attitudes toward AI, personality traits, and music-related variables influence evaluations. We further assess the influence of perceived humanness and analyze open-ended responses to uncover listener criteria for judging AI-generated music. Attitudes toward AI proved to be the best predictor of both liking and emotional intensity of AI-generated music. This quantitative finding was complemented by qualitative themes from our thematic analysis, which identified ethical, cultural, and contextual considerations as important criteria in listeners' evaluations of AI-generated music. Our results offer a nuanced view of how people experience music created by AI tools and point to key factors and methodological considerations for future research on music perception in human-AI interaction.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
