论文标题
音乐手势的互动机器学习
Interactive Machine Learning of Musical Gesture
论文作者
论文摘要
本章介绍了应用于音乐手势分析和设计的交互式机器学习（IML）技术的概述。我们经历了与捕获，分析和应用IML技术有关的主要挑战和需求，以使用声音合成系统执行人体手势。我们讨论如何使用不同的算法来完成不同的任务，包括与复杂的合成技术进行交互，并通过增强学习（RL）在我们开发的辅助交互式机器学习（AIML）中通过增强学习（RL）探索相互作用的可能性。我们以作者开发四个音乐作品的发展，以描述其中的一些技术的描述，以描述其中的某些技术，从而概述了IML对音乐实践的含义。
This chapter presents an overview of Interactive Machine Learning (IML) techniques applied to the analysis and design of musical gestures. We go through the main challenges and needs related to capturing, analysing, and applying IML techniques to human bodily gestures with the purpose of performing with sound synthesis systems. We discuss how different algorithms may be used to accomplish different tasks, including interacting with complex synthesis techniques and exploring interaction possibilities by means of Reinforcement Learning (RL) in an interaction paradigm we developed called Assisted Interactive Machine Learning (AIML). We conclude the chapter with a description of how some of these techniques were employed by the authors for the development of four musical pieces, thus outlining the implications that IML have for musical practice.
