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Riffusion adapts a text-to-image diffusion model to generate audio by generating spectrogram images and reconstructing waveforms.
Teerera kugwaro iriAI-yakarondedzerwa · ~2 min
It is a research and creative example; its outputs require listening and technical validation.
Released as a hobby project in 2022, Riffusion fine-tuned Stable Diffusion on paired text and spectrogram images. A spectrogram places time horizontally and frequency vertically, with pixel intensity representing magnitude or energy; this version uses a mel-frequency representation. The generated magnitude representation omits phase. Riffusion uses Griffin-Lim iterations to estimate phase and reconstruct a waveform, which can introduce audible artifacts. Its image-model adaptation demonstrates a route to audio generation, but does not guarantee musical quality or licensing status.
Exploring short musical sketches from text prompts
Comparing how prompt changes affect generated spectrogram patterns
Interpolating between prompt embeddings to explore transitions between sound ideas
Prototyping a musical idea before arranging or recording it in an audio workstation
Riffusion demonstrates one way to adapt an image-diffusion pipeline for audio by generating spectrogram images and reconstructing waveforms. The core project is marked no longer actively maintained. Generated clips should be checked for reconstruction artifacts and for rights appropriate to their intended use.
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Riffusion adapts a text-to-image diffusion model to generate audio by generating spectrogram images and reconstructing waveforms. It is a research and creative example; its outputs require listening and technical validation.
Riffusion yakanyatso-tuned Stable Diffusion, mufananidzo wekuparadzira modhi, kugadzira mifananidzo yespectrogram inozoshandurwa kuita odhiyo.
The spectrogram maps time horizontally and frequency vertically.
Iyo spectrogram inochengetedza ukuru asi inorasa chikamu, saka Griffin-Lim anofungidzira zvakare chikamu chekuvakazve inotamba waveform.
Riffusion’s pipeline supports prompt interpolation, allowing a transition between two prompt-conditioned generations.
Riffusion yakatanga sechirongwa chekuzvivaraidza naSeth Forsgren naHayk Martiros, chakaburitswa pachena mukupera kwa2022.
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InoteveraGaidhi rinotevera
DiffWave Diffusion Vocoder
AI Yenyaya