Abstract Sound Fusion with Unconditional Inversion Models
Not on the map. Why?
Abstract (arXiv)
An abstract sound is defined as a sound that does not disclose identifiable real-world sound events to a listener. Sound fusion aims to synthesize an original sound and a reference sound to generate a novel sound that exhibits auditory features beyond mere additive superposition of the sound constituents. To achieve this fusion, we employ inversion techniques that preserve essential features of the original sample while enabling controllable synthesis. We propose novel SDE and ODE inversion models based on DPMSolver++ samplers that reverse the sampling process by configuring model outputs as constants, eliminating circular dependencies incurred by noise prediction terms. Our inversion approach requires no prompt conditioning while maintaining flexible guidance during sampling.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 12 of its 15 references that are in the map. First posted on arXiv 13 Jun 2025.
Builds on
12 of 15 references.
References · 12
- 2020Denoising Diffusion Probabilistic Modelscited by 21,076
- 2022DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Stepscited by 1,979
- 2021SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equationscited by 1,937
- 2021Pivotal Tuning for Latent-based Editing of Real Imagescited by 427
- 2016Generative Visual Manipulation on the Natural Image Manifoldcited by 348
- 2022EDICT: Exact Diffusion Inversion via Coupled Transformationscited by 258
- 2024Fast Timing-Conditioned Latent Audio Diffusioncited by 181
- 2023AUDIT: Audio Editing by Following Instructions with Latent Diffusion Modelscited by 83
- 2024Zero-Shot Unsupervised and Text-Based Audio Editing Using DDPM Inversioncited by 60
- 2024BELM: Bidirectional Explicit Linear Multi-step Sampler for Exact Inversion in Diffusion Modelscited by 29
- 2020A Differentiable Perceptual Audio Metric Learned from Just Noticeable Differencescited by 23
- 2024Prompt-guided Precise Audio Editing with Diffusion Modelscited by 18
Built on by
Not cited yet.
Similar, not cited
Close in wording, no citation either way
- 2026Off-manifold robustness in synthesizer inversion with joint distribution flow matching
- 2026AudioX-Turbo: A Unified Framework for Efficient Anything-to-Audio Generation
- 2025Audio Palette: A Diffusion Transformer with Multi-Signal Conditioning for Controllable Foley Synthesis
- 2025Audio synthesizer inversion in symmetric parameter spaces with approximately equivariant flow matching
- 2026DDSynth-RL: Audio Synthesizer Inversion via Discrete Diffusion with Reinforcement Learning
- 2023EDMSound: Spectrogram Based Diffusion Models for Efficient and High-Quality Audio Synthesis
- 2026Mix2Morph: Learning Sound Morphing from Noisy Mixes
- 2023Controllable Music Production with Diffusion Models and Guidance Gradients