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An AudioWorklet-based signal engine for a live coding language ecosystem

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conference contribution
posted on 2023-06-09, 19:17 authored by Francisco Bernardo, Chris KieferChris Kiefer, Thor MagnussonThor Magnusson
This 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

2663-5844

Publisher

WAC

Page range

77-82

Event name

Web Audio Conference

Event location

Norwegian University of Science and Technology (NTNU), Trondheim, Norway

Event type

conference

Event date

4-6 December 2019

Department affiliated with

  • Music Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Editors

Gerard Roma

Legacy Posted Date

2019-10-10

First Open Access (FOA) Date

2020-05-28

First Compliant Deposit (FCD) Date

2019-10-07

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