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Fast Timing-Conditioned Latent Audio Diffusion

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arxiv 2402.04825 v3 pith:AYGY35X3 submitted 2024-02-07 cs.SD cs.LGeess.AS

Fast Timing-Conditioned Latent Audio Diffusion

classification cs.SD cs.LGeess.AS
keywords audiomusicstereolatentpromptssoundstextdiffusion
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Generating long-form 44.1kHz stereo audio from text prompts can be computationally demanding. Further, most previous works do not tackle that music and sound effects naturally vary in their duration. Our research focuses on the efficient generation of long-form, variable-length stereo music and sounds at 44.1kHz using text prompts with a generative model. Stable Audio is based on latent diffusion, with its latent defined by a fully-convolutional variational autoencoder. It is conditioned on text prompts as well as timing embeddings, allowing for fine control over both the content and length of the generated music and sounds. Stable Audio is capable of rendering stereo signals of up to 95 sec at 44.1kHz in 8 sec on an A100 GPU. Despite its compute efficiency and fast inference, it is one of the best in two public text-to-music and -audio benchmarks and, differently from state-of-the-art models, can generate music with structure and stereo sounds.

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Forward citations

Cited by 8 Pith papers

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  3. How Do Diffusion Classifiers Decide? A Bias-Centric Evaluation

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