Pierce Charlotte, Hendtlass Tim, Bartel Anthony, Woodward Clinton J
Melbourne School of Engineering, The University of Melbourne, Parkville, VI, Australia.
Faculty of Science, Engineering and Technology, Swinburne University of Technology, Hawthorn, VI, Australia.
Front Artif Intell. 2021 Jan 27;3:497530. doi: 10.3389/frai.2020.497530. eCollection 2020.
Sight reading skills are widely considered to be crucial for all musicians. However, given that sight reading involves playing sheet music without having seen it before, once an exercise has been completed by a student it can no longer be used as a sight reading exercise for them. In this paper we present a novel evolutionary algorithm for generating musical sight reading exercises in the Western art music tradition. Using models based on expert examples, the algorithm generates material suitable for practice which is both technically appropriate and aesthetically pleasing with respect to an instrument and difficulty level. This overcomes the resource constraint in using traditional practice exercises, which are exhausted quickly by students and teachers due to their limited quantity.
视奏技巧被广泛认为对所有音乐家都至关重要。然而，由于视奏涉及演奏之前从未见过的乐谱，一旦学生完成了一项练习，它就不能再作为他们的视奏练习了。在本文中，我们提出了一种新颖的进化算法，用于生成西方艺术音乐传统中的音乐视奏练习。该算法使用基于专家示例的模型，生成适合练习的材料，这些材料在技术上适合且在美学上符合某种乐器和难度水平的要求。这克服了使用传统练习曲目的资源限制，因为传统练习曲目数量有限，很快就会被学生和教师用完。
