My graduate research focused on evolutionary algorithms and their applications to audio digital signal processing and computer music. Genetic and evolutionary algorithms are an alternative machine learning framework (compared to neural networks and deep learning) that can solve complex DSP tasks such as signal reproduction and digital filter design.
This research culminated in the development and release of (FaustCGP), a free software program that can generate new DSP computer programs that meet certain criteria, such as a target sound or instrument output from an audio synthesizer or an impulse or frequency response of an IIR filter. These newly generated programs can then be put into practical use through the production of new music or other audio applications.
Publications
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Journal Articles
- Edward Ly and Julián Villegas, “Cartesian Genetic Programming Parameterization in the Context of Audio Synthesis,” IEEE Signal Processing Letters, vol. 30, pp. 1077–1081, Aug. 2023.
- Edward Ly and Julián Villegas, “Generating Artificial Reverberation via Genetic Algorithms for Real-Time Applications,” Entropy, vol. 22, no. 11, pp. 1-19, Nov. 2020.
Conference Proceedings
- Peter Kudry, Edward Ly, Kevin Manuel Diaz España, Chiu Ming-Jung, Masaki Soga, and Debopriyo Roy, “Metaverse in Education for Students with Disabilities,” in 2nd International Conference on Entertainment Technology and Management (ICETM2023), AIP Publishing, Nov. 2023, pp. 1-8.
- Edward Ly and Julián Villegas, “Digital Filter Design via Recurrent Cartesian Genetic Programming,” in 13th International Workshop on Computational Intelligence and Applications (IWCIA2023), Hiroshima, Japan: IEEE, Nov. 2023, pp. 7–12.
- Edward Ly and Julián Villegas, “Additive Synthesis via Recurrent Cartesian Genetic Programming in FAUST,” in 153rd Audio Engineering Society Convention, New York, Oct. 2022, pp. 1–7.
- Edward Ly and Julián Villegas, “Genetic Reverb: Synthesizing Artificial Reverberant Fields via Genetic Algorithms,” in 9th International Conference on Computational Intelligence in Music, Sound, Art and Design (EvoMUSART 2020), Cham: Springer, Apr. 2020, pp. 90–103.
