如果图灵与人工伙伴弹钢琴
If Turing played piano with an artificial partner
AI总结：
本研究探讨基于变分自编码器的人工音乐伙伴能否提供令人信服的社交体验，发现交互性而非生成复杂性对社交AI更重要。
摘要：
音乐是一种固有的社交活动，允许人们分享体验并感到彼此相连。在设计能够展现出与真人合奏相似社交体验的人工伙伴方面，进展甚微。实现生成式模型的神经网络架构（如大型语言模型）适合生成乐谱。然而，社交性音乐演奏不仅仅是演奏乐谱，它还必须补充其他音乐家的想法并正确把握时间。我们探讨了这样一个问题：通过训练生成乐谱的生成式模型（不一定针对同步和延续进行优化）是否能实现令人信服的社交体验。该网络是一个在大型数字乐谱语料库上训练的变分自编码器，被适配用于与人类伙伴进行定时的呼应任务。参与者在不同配置下与人类或人工伙伴弹钢琴，并对演奏质量和自我-他人整合的第一人称体验进行评分。总体而言，人工伙伴表现出潜力，但评分低于人类伙伴。具有最简单设计和最高相似性参数的人工伙伴在某些指标上与人类伙伴没有差异，这表明在实现社交AI方面，交互性而非生成复杂性更为重要。
英文摘要：
Music is an inherently social activity that allows people to share experiences and feel connected with one another. There has been little progress in designing artificial partners exhibiting a similar social experience as playing with another person. Neural network architectures that implement generative models, such as large language models, are suited for producing musical scores. Playing music socially, however, involves more than playing a score; it must complement the other musicians' ideas and keep time correctly. We addressed the question of whether a convincing social experience is made possible by a generative model trained to produce musical scores, not necessarily optimized for synchronization and continuation. The network, a variational autoencoder trained on a large corpus of digital scores, was adapted for a timed call-and-response task with a human partner. Participants played piano with a human or artificial partner-in various configurations-and rated the performance quality and first-person experience of self-other integration. Overall, the artificial partners held promise but were rated lower than human partners. The artificial partner with simplest design and highest similarity parameter was not rated differently from the human partners on some measures, suggesting that interactive rather than generative sophistication is important in enabling social AI.
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。
