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We release synth1B1, a multi-modal audio corpus consisting of 1 billion4-second synthesized sounds, paired with the synthesis parameters used togenerate them. The dataset is 100x larger than any audio dataset in theliterature. We also introduce torchsynth, an open source modular synthesizerthat 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 synthtimbre and subtractive synth pitch. Using these datasets, we demonstrate newrank-based evaluation criteria for existing audio representations. Finally, wepropose a novel approach to synthesizer hyperparameter optimization.

One Billion Audio Sounds from GPU-enabled Modular Synthesis