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.

中文翻译：

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手势的交互式机器学习

本章概述了应用于音乐手势分析和设计的交互式机器学习（IML）技术。我们将经历与捕获，分析IML技术并将其应用于人体手势有关的主要挑战和需求，以实现声音合成系统的目的。我们讨论了如何使用不同的算法来完成不同的任务，包括与复杂的综合技术进行交互以及在我们开发的称为“交互式交互机器学习（AIML）”的交互范式中借助强化学习（RL）探索交互可能性。我们在本章结束时描述了作者是如何使用其中的一些技巧来开发四首音乐作品的，从而概述了IML对音乐实践的影响。