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A Signal Engine for a Live Coding Language Ecosystem

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This paper reports on early advances in the design of a browser-based ecosystem for creating new live coding languages, optimal for audio synthesis, machine learning, and machine listening. We present the rationale and challenges when applying the Web Audio API to the design of a high-performance signal synthesis engine, using an AudioWorklet-based solution and refactoring our digital signal processing library Maximilian.js. Furthermore, we contribute with the latest advances in Sema, a new user-friendly playground that integrates the signal engine to empower the live coding community to design their own idiosyncratic languages and interfaces. The evaluation shows that the system runs with high reliability and efficiency and low latency.

JAES Volume 68 Issue 10 pp. 756-766; October 2020
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AES - Audio Engineering Society