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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.
Author (s): Bernardo, Francisco; Kiefer, Chris; Magnusson, Thor
Affiliation:
Experimental Music Technologies Lab / Department of Music, University of Sussex, Brighton, UK
(See document for exact affiliation information.)
Publication Date:
2020-10-06
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Bernardo, Francisco; Kiefer, Chris; Magnusson, Thor; 2020; A Signal Engine for a Live Coding Language Ecosystem [PDF]; Experimental Music Technologies Lab / Department of Music, University of Sussex, Brighton, UK; Paper ; Available from: https://aes2.org/publications/elibrary-page/?id=20992
Bernardo, Francisco; Kiefer, Chris; Magnusson, Thor; A Signal Engine for a Live Coding Language Ecosystem [PDF]; Experimental Music Technologies Lab / Department of Music, University of Sussex, Brighton, UK; Paper ; 2020 Available: https://aes2.org/publications/elibrary-page/?id=20992