评测音乐创作AI系统MMM-C的可用性与用户接受度，发现专家与爱好者体验相似。
Evaluating Human-AI Interaction via Usability, User Experience and Acceptance Measures for MMM-C: A Creative AI System for Music Composition
- 将AI音乐生成工具嵌入Cubase，通过单参数插件实现人机共创。
- 用户评分显示易用性与接受度高，但控制力和可预测性仍不足。
- 适用于音乐创作者评估人机协作系统的用户体验设计。
随着人工智能的发展，艺术领域中的人机协同创作日益受到关注，尤其在音乐创作方面，AI系统已能生成媲美人类的作品。本文深入评估了多轨音乐机器（Multi-Track Music Machine, MMM）作为协同创作工具在音乐作曲中的用户采纳情况。为此，我们通过开发名为MMM-Cubase（MMM-C）的单参数插件，将该系统集成至Steinberg公司流行的数字音频工作站（DAW）Cubase中，实现人机共同作曲。研究采用三部分混合方法，针对两类高水平作曲者——业余爱好者与专业人士——分别测量系统的可用性、用户体验及技术接受度。结果显示，用户在易用性和接受度方面评分积极，普遍感受到新颖性、惊喜感与操作简便性；然而，在音乐生成过程中仍存在控制力与可预测性方面的局限。值得注意的是，两组用户间无显著差异。
原文摘要 · Abstract (English)
With the rise of artificial intelligence (AI), there has been increasing interest in human-AI co-creation in a variety of artistic domains including music as AI-driven systems are frequently able to generate human-competitive artifacts. Now, the implications of such systems for musical practice are being investigated. We report on a thorough evaluation of the user adoption of the Multi-Track Music Machine (MMM) as a co-creative AI tool for music composers. To do this, we integrate MMM into Cubase, a popular Digital Audio Workstation (DAW) by Steinberg, by producing a "1-parameter" plugin interface named MMM-Cubase (MMM-C), which enables human-AI co-composition. We contribute a methodological assemblage as a 3-part mixed method study measuring usability, user experience and technology acceptance of the system across two groups of expert-level composers: hobbyists and professionals. Results show positive usability and acceptance scores. Users report experiences of novelty, surprise and ease of use from using the system, and limitations on controllability and predictability of the interface when generating music. Findings indicate no significant difference between the two user groups.
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