mlsanityData to 7 Oct 2026

Sound2Synth: Interpreting Sound via FM Synthesizer Parameters Estimation

arXiv 2205.03043 ↗First posted 6 May 2022cs.SD cs.AI cs.LGcited by 7

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Abstract (arXiv)

Synthesizer is a type of electronic musical instrument that is now widely used in modern music production and sound design. Each parameters configuration of a synthesizer produces a unique timbre and can be viewed as a unique instrument. The problem of estimating a set of parameters configuration that best restore a sound timbre is an important yet complicated problem, i.e.: the synthesizer parameters estimation problem. We proposed a multi-modal deep-learning-based pipeline Sound2Synth, together with a network structure Prime-Dilated Convolution (PDC) specially designed to solve this problem. Our method achieved not only SOTA but also the first real-world applicable results on Dexed synthesizer, a popular FM synthesizer.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 6 of its 27 references that are in the map. First posted on arXiv 6 May 2022.

Builds on

6 of 27 references.

References · 6

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  3. 2016Densely Connected Convolutional Networkscited by 6,691
  4. 2020DDSP: Differentiable Digital Signal Processingcited by 177
  5. 2019Universal audio synthesizer control with normalizing flowscited by 16
  6. 2021SerumRNN: Step by Step Audio VST Effect Programmingcited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 1; 2024: 0; 2025: 2; 2026: 2.

7 papers.