论文标题
通过自适应可视化和数字增强，钢琴学习和即兴创作
Piano Learning and Improvisation through Adaptive Visualisation and Digital Augmentation
论文作者
论文摘要
对于新手，专家和技术人员来说，学习钢琴的任务一直是数百年来的挑战。引入了几项创新，以支持适当的姿势，运动和动机，而视觉阅读和即兴创作仍然是最不探索的领域。在该博士学位中，我们通过将钢琴增强为交互式和适应性空间来解决这一差距。具体来说，我们将通过两种良好的方法来探讨如何通过自适应可视化的学习者来支持学习者：（1）通过基于学习者的能力来设计自适应可视化，以支持常规的钢琴演奏，（2）通过在钢琴上预测的专家注释来鼓励他们鼓励即兴演奏。为此，我们将建立一个模型，以了解学习者时空数据的复杂性，并使用这些模型来支持学习。然后，我们将通过用户研究来评估我们的方法，从而实现实践和即兴创作。我们的工作有助于自适应可视化如何推动音乐仪器学习并支持沉浸式空间中的多目标选择任务。
The task of learning the piano has been a centuries-old challenge for novices, experts and technologists. Several innovations have been introduced to support proper posture, movement, and motivation, while sight-reading and improvisation remain the least-explored areas. In this PhD, we address this gap by redesigning the piano augmentation as an interactive and adaptive space. Specifically, we will explore how to support learners with adaptive visualisations through a two-pronged approach: (1) by designing adaptive visualisations based on the proficiency of the learner to support regular piano playing and (2) by assisting them with expert annotations projected on the piano to encourage improvisation. To this end, we will build a model to understand the complexities of learners' spatiotemporal data and use these to support learning. We will then evaluate our approach through user studies enabling practice and improvisation. Our work contributes to how adaptive visualisations can push music instrument learning and support multi-target selection tasks in immersive spaces.
