In recent years, text-to-music models have been the biggest breakthrough in automatic music generation. While they are unquestionably a showcase of technological progress, it is not clear yet how they can be realistically integrated into the artistic practice of musicians and music practitioners. This paper aims to address this question via Prompt Audio Generation User Research Investigation (PAGURI), a user experience study where we leverage recent text-to-music developments to study how musicians and practitioners interact with these systems, evaluating their satisfaction levels. We developed an online tool through which users can generate music samples and/or apply recently proposed personalization techniques, based on fine-tuning, to make the text-to-music model generate sounds closer to their needs and preferences. Using questionnaires, we analyzed how participants interacted with the proposed tool, to understand the effectiveness of text-to-music models in enhancing users' creativity. Results show that even if the audio samples generated and their quality may not always meet user expectations, the majority of the participants would incorporate the tool in their creative process. Furthermore, they provided insights into potential enhancements for the system and its integration into their music practice.

翻译：近年来，文本到音乐模型已成为自动音乐生成领域的最大突破。尽管这些模型无疑是技术进步的重要体现，但其如何切实融入音乐家及从业者的艺术实践尚不明确。本文旨在通过"提示音频生成用户研究调查"（PAGURI）这一用户体验研究来探讨该问题。我们借助最新的文本到音乐技术进展，研究音乐从业者如何与这类系统交互，并评估其满意度。我们开发了一款在线工具，用户可通过该工具生成音乐样本，并/或应用基于微调的最新个性化技术，使文本到音乐模型生成更符合其需求与偏好的声音。通过问卷调查，我们分析了参与者如何使用该工具，以理解文本到音乐模型在提升用户创造力方面的有效性。结果表明，尽管生成的音频样本及其质量可能并不总能满足用户期望，但大多数参与者仍愿意将该工具纳入其创作流程。此外，他们还为系统优化及其与音乐实践的融合提供了改进建议。