We release synth1B1, a multi-modal audio corpus consisting of 1 billion 4-second synthesized sounds, which is 100x larger than any audio dataset in the literature. Each sound is paired with the corresponding latent parameters used to generate it. synth1B1 samples are deterministically generated on-the-fly  16200x faster than real-time (714MHz) on a single GPU using torchsynth URL an open-source modular synthesizer we release. Additionally , we release two new audio datasets: FM synth timbre URL and subtractive synth pitch URL Using these datasets, we demonstrate new rank-based synthesizer-motivated evaluation criteria for existing audio representations. Finally, we propose novel approaches to synthesizer hyperparameter optimization , and demonstrate how perceptually-correlated auditory distances could enable new applications in synthesizer design .
We release synth1B1, a multi-modal audio corpus consisting of 1 billion 4-second synthesized sounds, paired with the synthesis parameters used to generate them. The dataset is 100x larger than any audio dataset in the literature. We also introduce torchsynth, an open source modular synthesizer that generates the synth1B1 samples on-the-fly at 16200x faster than real-time (714MHz) on a single GPU . Finally , we release two new audio datasets: FM synth timbre and subtractive synth pitch . Using these datasets, we demonstrate new rank-based evaluation criteria for existing audio representations. Finally, we propose a novel approach to synthesizer hyperparameter optimization .
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, and demonstrate how perceptually-correlated auditory distances could enable new applications in synthesizer design