WAC_2019_FB_CK_TM_camera-ready.pdf (1.24 MB)
An AudioWorklet-based signal engine for a live coding language ecosystem
conference contribution
posted on 2023-06-09, 19:17 authored by Francisco Bernardo, Chris KieferChris Kiefer, Thor MagnussonThor MagnussonThis paper reports on early advances in the design of an ecosystem for creating new live coding languages, optimal for audio synthesis, machine learning and machine listening. We present the design rationale and challenges when applying the Web Audio API, and in particular, an AudioWorklet-based solution to refactoring our digital signal processing library Maximilian.js for our high-performance signal synthesis engine. Furthermore, we contribute with a new system implementation, engineered for modern web applications, and for the live coding community to design their own idiosyncratic languages and interfaces applying our signal engine. The evaluation shows that the system runs with high reliability, efficiency and low latency.
Funding
MIMIC: Musically Intelligent Machines Interacting Creatively; G2434; AHRC-ARTS & HUMANITIES RESEARCH COUNCIL; AH/R002657/1
History
Publication status
- Published
File Version
- Accepted version
Journal
Proceedings of Web Audio Conference (WAC-2019)ISSN
2663-5844Publisher
WACPublisher URL
Page range
77-82Event name
Web Audio ConferenceEvent location
Norwegian University of Science and Technology (NTNU), Trondheim, NorwayEvent type
conferenceEvent date
4-6 December 2019Department affiliated with
- Music Publications
Full text available
- Yes
Peer reviewed?
- Yes
Editors
Gerard RomaLegacy Posted Date
2019-10-10First Open Access (FOA) Date
2020-05-28First Compliant Deposit (FCD) Date
2019-10-07Usage metrics
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