EarSketch : Teaching computational music remixing in an online Web Audio based learning environment
EarSketch : Teaching computational music remixing in an online Web Audio based learning environment
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EarSketch：在基于网络音频的在线学习环境中教授计算音乐混音
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Jason Freeman
中科院分区：
文献类型：
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作者：
A. Mahadevan;Jason Freeman;Jason Freeman
EarSketch是一种通过数字音频工作站范例中的算法音乐创作和混音来教授计算机科学概念的新方法。该项目包括一个Python/JavaScript编码环境，一个数字音频工作站视图，一个音频循环浏览器，一个社交共享网站和一个综合课程。EarSketch旨在满足计算机音乐和计算机科学入门课程的艺术和教学目标。事实证明，这个集成平台在通过音乐创作吸引文化和经济多元化的学生参与计算方面特别有效。EarSketch使用Web Audio API作为其主要的音频引擎，用于音频数据的回放、效果处理和离线渲染。本文详细探讨了EarSketch的技术框架，并讨论了使用Web Audio API实现该项目所带来的机遇和挑战。
EarSketch is a novel approach to teaching computer science concepts via algorithmic music composition and remixing in the context of a digital audio workstation paradigm. This project includes a Python/Javascript coding environment, a digital audio workstation view, an audio loop browser, a social sharing site and an integrated curriculum. EarSketch is aimed at satisfying both artistic and pedagogical goals of introductory courses in computer music and computer science. This integrated platform has proven particularly effective at engaging culturally and economically diverse students in computing through music creation. EarSketch makes use of the Web Audio API as its primary audio engine for playback, effects processing and offline rendering of audio data. This paper explores the technical framework of EarSketch in greater detail and discusses the opportunities and challenges associated with using the Web Audio API to realize the project.