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This study presents a novel audio effect plugin that generates virtual acoustic spaces using a Genetic Algorithm (GA). The plugin creates synthetic Room Impulse Responses (RIRs), offering users control over acoustic parameters for unique sound environments.

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Area of Science:

  • Digital Signal Processing
  • Acoustics
  • Artificial Intelligence

Background:

  • Convolution reverb is crucial for realistic audio effects.
  • Generating diverse and controllable Room Impulse Responses (RIRs) is challenging.
  • Existing methods may not offer sufficient control over acoustic parameters.

Purpose of the Study:

  • To develop a Virtual Studio Technology (VST) 2 audio effect plugin for convolution reverb.
  • To utilize a Genetic Algorithm (GA) for generating synthetic Room Impulse Responses (RIRs).
  • To enable user control over RIRs using ISO 3382-1 standard parameters.

Main Methods:

  • A Genetic Algorithm (GA) evolves synthetic RIRs from Gaussian noise.
  • GA employs truncation selection, weighted average crossover, and Gaussian multiplication mutation.
  • Binaural Room Impulse Responses (BRIRs) are generated for stereo output.
  • ISO 3382-1 parameters (reverberation time, clarity) guide RIR fitness.

Main Results:

  • Objective evaluation confirmed that contradictory parameter combinations yield low-fitness RIRs.
  • Subjective evaluation showed GA-generated RIRs are perceptually distinguishable from real ones.
  • Perceptual differences decreased with longer GA execution times and speech-only signals.

Conclusions:

  • The proposed VST plugin effectively generates controllable synthetic RIRs and BRIRs.
  • The GA approach allows for the creation of novel virtual acoustic spaces.
  • Further optimization of GA parameters can enhance the perceptual realism of synthetic RIRs.