# Differentiable Wavetable Synthesis

arXiv: https://arxiv.org/abs/2111.10003 · HTML: https://mlsanity.com/paper/2111.10003/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 28 references that are in the map.
- First posted on arXiv 19 Nov 2021.

## Builds on (most cited first, 14 of 14)

- [Distributed Representations of Words and Phrases and their Compositionality](https://mlsanity.com/paper/1310.4546/) (2013)
- [WaveNet: A Generative Model for Raw Audio](https://mlsanity.com/paper/1609.03499/) (2016)
- [FastSpeech 2: Fast and High-Quality End-to-End Text to Speech](https://mlsanity.com/paper/2006.04558/) (2020)
- [Neural Turing Machines](https://mlsanity.com/paper/1410.5401/) (2014)
- [Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders](https://mlsanity.com/paper/1704.01279/) (2017)
- [Efficient Neural Audio Synthesis](https://mlsanity.com/paper/1802.08435/) (2018)
- [DDSP: Differentiable Digital Signal Processing](https://mlsanity.com/paper/2001.04643/) (2020)
- [GANSynth: Adversarial Neural Audio Synthesis](https://mlsanity.com/paper/1902.08710/) (2019)
- [CREPE: A Convolutional Representation for Pitch Estimation](https://mlsanity.com/paper/1802.06182/) (2018)
- [Creating A Multi-track Classical Musical Performance Dataset for Multimodal Music Analysis: Challenges, Insights, and Applications](https://mlsanity.com/paper/1612.08727/) (2016)
- [Differentiable Artificial Reverberation](https://mlsanity.com/paper/2105.13940/) (2021)
- [Differentiable Signal Processing With Black-Box Audio Effects](https://mlsanity.com/paper/2105.04752/) (2021)
- [Meta-Neighborhoods](https://mlsanity.com/paper/1909.09140/) (2019)
- [Real-time Timbre Transfer and Sound Synthesis using DDSP](https://mlsanity.com/paper/2103.07220/) (2021)

## Built on by (most cited first, 4 of 4)

- [GANStrument: Adversarial Instrument Sound Synthesis with Pitch-invariant Instance Conditioning](https://mlsanity.com/paper/2211.05385/) (2022)
- [DiffMoog: a Differentiable Modular Synthesizer for Sound Matching](https://mlsanity.com/paper/2401.12570/) (2024)
- [HyperGANStrument: Instrument Sound Synthesis and Editing with Pitch-Invariant Hypernetworks](https://mlsanity.com/paper/2401.04558/) (2024)
- [Sines, Transient, Noise Neural Modeling of Piano Notes](https://mlsanity.com/paper/2409.06513/) (2024)

## Abstract (arXiv)

Differentiable Wavetable Synthesis (DWTS) is a technique for neural audio synthesis which learns a dictionary of one-period waveforms i.e. wavetables, through end-to-end training. We achieve high-fidelity audio synthesis with as little as 10 to 20 wavetables and demonstrate how a data-driven dictionary of waveforms opens up unprecedented one-shot learning paradigms on short audio clips. Notably, we show audio manipulations, such as high quality pitch-shifting, using only a few seconds of input audio. Lastly, we investigate performance gains from using learned wavetables for realtime and interactive audio synthesis.