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New SCAPES model generates environmental sounds efficiently

By PulseAugur Editorial · [1 sources] ·

Researchers have developed SCAPES, a new generative model for environmental sounds that is lightweight and resource-efficient. This model synthesizes high-fidelity environmental textures using high-level semantic control by operating on the continuous latent manifold of a neural audio codec. SCAPES utilizes a Continuous Normalizing Flow with Flow Matching to model latent trajectories, allowing a 36-million parameter instance to be trained on limited datasets using a single consumer-grade GPU. AI

IMPACT This model offers a more accessible and flexible tool for creative sound design and open research by reducing computational and ecological costs.

RANK_REASON The item is a research paper detailing a new generative model for environmental sounds. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New SCAPES model generates environmental sounds efficiently

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The item is a research paper detailing a new generative model for environmental sounds. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Esteban Guti\'errez, Lonce Wyse, Frederic Font, Xavier Serra ·

    SCAPES: Semantically Conditioned Autoregressive Prior for Environmental Sounds

    arXiv:2609.04634v1 Announce Type: cross Abstract: As generative audio models grow in complexity, the computational and ecological costs of synthesizing everyday sounds have become increasingly prohibitive, often requiring industrial-scale resources and massive datasets. In this p…

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