One Billion Audio Sounds from GPU-enabled Modular Synthesis
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Abstract (arXiv)
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.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 24 of its 41 references that are in the map. First posted on arXiv 27 Apr 2021.
Builds on
24 of 41 references.
References · 24
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12 more
- 2013A Theoretical Analysis of NDCG Type Ranking Measurescited by 119
- 2021BYOL for Audio: Self-Supervised Learning for General-Purpose Audio Representationcited by 106
- 2019Neural source-filter waveform models for statistical parametric speech synthesiscited by 46
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- 2020I'm Sorry for Your Loss: Spectrally-Based Audio Distances Are Bad at Pitchcited by 17
- 2019Universal audio synthesizer control with normalizing flowscited by 16
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Built on by
Citing papers per year: 2021: 1; 2022: 3; 2023: 0; 2024: 4; 2025: 3.
11 papers.
- 2022Masked Modeling Duo: Learning Representations by Encouraging Both Networks to Model the Inputcited by 23
- 2024Differentiable All-pole Filters for Time-varying Audio Systemscited by 7
- 2022TimbreCLIP: Connecting Timbre to Text and Imagescited by 5
- 2021Neural Synthesis of Footsteps Sound Effects with Generative Adversarial Networkscited by 4
- 2024Investigating Design Choices in Joint-Embedding Predictive Architectures for General Audio Representation Learningcited by 4
- 2024Creative Text-to-Audio Generation via Synthesizer Programmingcited by 4
- 2024Contrastive Learning from Synthetic Audio Doppelg"angerscited by 1
- 2025Modulation Discovery with Differentiable Digital Signal Processingcited by 1
- 2022Learning Audio Representations with MLPscited by 0
- 2025Neural Proxies for Sound Synthesizers: Learning Perceptually Informed Preset Representationscited by 0
- 2025AaSP: Aliasing-aware Self-Supervised Pre-Training for Audio Spectrogram Transformerscited by 0
- 2025AaSP: Aliasing-aware Self-Supervised Pre-Training for Audio Spectrogram Transformers3 Dec 2025
- 2025Modulation Discovery with Differentiable Digital Signal Processing7 Oct 2025
- 2025Neural Proxies for Sound Synthesizers: Learning Perceptually Informed Preset Representations9 Sep 2025
- 2024Contrastive Learning from Synthetic Audio Doppelg"angers9 Jun 2024
- 2024Creative Text-to-Audio Generation via Synthesizer Programming1 Jun 2024
- 2024Investigating Design Choices in Joint-Embedding Predictive Architectures for General Audio Representation Learning14 May 2024
- 2024Differentiable All-pole Filters for Time-varying Audio Systems11 Apr 2024
- 2022TimbreCLIP: Connecting Timbre to Text and Images21 Nov 2022
- 2022Masked Modeling Duo: Learning Representations by Encouraging Both Networks to Model the Input26 Oct 2022
- 2022Learning Audio Representations with MLPs16 Mar 2022
- 2021Neural Synthesis of Footsteps Sound Effects with Generative Adversarial Networks18 Oct 2021