A Signal Engine for a Live Coding Language Ecosystem
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F. Bernardo, C. Kiefer, and T. Magnusson, "A Signal Engine for a Live Coding Language Ecosystem," J. Audio Eng. Soc., vol. 68, no. 10, pp. 756-766, (2020 October.). doi: https://doi.org/10.17743/jaes.2020.0016
F. Bernardo, C. Kiefer, and T. Magnusson, "A Signal Engine for a Live Coding Language Ecosystem," J. Audio Eng. Soc., vol. 68 Issue 10 pp. 756-766, (2020 October.). doi: https://doi.org/10.17743/jaes.2020.0016
Abstract: 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.
@article{bernardo2020a,
author={bernardo, francisco and kiefer, chris and magnusson, thor},
journal={journal of the audio engineering society},
title={a signal engine for a live coding language ecosystem},
year={2020},
volume={68},
number={10},
pages={756-766},
doi={https://doi.org/10.17743/jaes.2020.0016},
month={october},}
@article{bernardo2020a,
author={bernardo, francisco and kiefer, chris and magnusson, thor},
journal={journal of the audio engineering society},
title={a signal engine for a live coding language ecosystem},
year={2020},
volume={68},
number={10},
pages={756-766},
doi={https://doi.org/10.17743/jaes.2020.0016},
month={october},
abstract={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.},}
TY - paper
TI - A Signal Engine for a Live Coding Language Ecosystem
SP - 756
EP - 766
AU - Bernardo, Francisco
AU - Kiefer, Chris
AU - Magnusson, Thor
PY - 2020
JO - Journal of the Audio Engineering Society
IS - 10
VO - 68
VL - 68
Y1 - October 2020
TY - paper
TI - A Signal Engine for a Live Coding Language Ecosystem
SP - 756
EP - 766
AU - Bernardo, Francisco
AU - Kiefer, Chris
AU - Magnusson, Thor
PY - 2020
JO - Journal of the Audio Engineering Society
IS - 10
VO - 68
VL - 68
Y1 - October 2020
AB - 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.
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.
Authors:
Bernardo, Francisco; Kiefer, Chris; Magnusson, Thor
Affiliation:
Experimental Music Technologies Lab / Department of Music, University of Sussex, Brighton, UK JAES Volume 68 Issue 10 pp. 756-766; October 2020
Publication Date:
November 30, 2020Import into BibTeX
Permalink:
http://www.aes.org/e-lib/browse.cfm?elib=20992