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Genetic Reverb: Synthesizing Artificial Reverberant Fields via Genetic Algorithms

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Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12103))

Abstract

We present Genetic Reverb, a user-friendly vst 2 audio effect plugin that performs convolution with Room Impulse Responses (rirs) generated via a Genetic Algorithm (ga). The parameters of the plugin include some of the standard room acoustics parameters mapped to perceptual correlates (decay time, intimacy, clarity, warmth, among others). These parameters provide the user with some control over the resulting rirs as they determine the fitness values of potential rirs. In the ga, these rirs are initially generated via a Gaussian noise method, and then evolved via truncation selection, multi-point crossover, zero-value mutation, and Gaussian mutation. These operations repeat until a certain number of generations has passed or the fitness value reaches a threshold. Either way, the best-fit rir is returned. The user can also generate two different rirs simultaneously, and assign each of them to the left and right stereo channels for a binaural reverberation effect. With Genetic Reverb, the user can generate and store new rirs that represent virtual rooms, some of which may even be impossible to replicate in the physical world. An original musical composition using the Genetic Reverb plugin is presented to demonstrate its applications. (The source code and link to the demo track is available at https://github.com/edward-ly/GeneticReverb).

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Acknowledgements

The authors thank the Audio Engineering Society for hosting the 2nd ever Matlab Plugin Student Competition at the 147th Convention in New York 2019, Mathworks for providing the travel grants for this competition, and the judges of this competition for their valuable comments.

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Authors and Affiliations

  1. University of Aizu, Aizu-Wakamatsu, Fukushima, 965-8580, Japan

    Edward Ly & Julián Villegas

Authors
  1. Edward Ly
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  2. Julián Villegas
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Corresponding author

Correspondence to Edward Ly .

Editor information

Editors and Affiliations

  1. University of A Coruña, A Coruña, Spain

    Juan Romero

  2. Aston University, Birmingham, UK

    Anikó Ekárt

  3. University of Coimbra, Coimbra, Portugal

    Tiago Martins

  4. University of Coimbra, Coimbra, Portugal

    João Correia

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Ly, E., Villegas, J. (2020). Genetic Reverb: Synthesizing Artificial Reverberant Fields via Genetic Algorithms. In: Romero, J., Ekárt, A., Martins, T., Correia, J. (eds) Artificial Intelligence in Music, Sound, Art and Design. EvoMUSART 2020. Lecture Notes in Computer Science(), vol 12103. Springer, Cham. https://doi.org/10.1007/978-3-030-43859-3_7

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  • DOI: https://doi.org/10.1007/978-3-030-43859-3_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-43858-6

  • Online ISBN: 978-3-030-43859-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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