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Research questionHow can environmental-audio generators provide semantic control under limited compute and training data?Generating everyday sounds with meaningful semantic control can require substantial computation and large, carefully curated datasets. These requirements make controllable environmental-audio synthesis difficult when training resources and data are limited.
AI
Audio & Speech
Audio & Speech Processing
Machine Learning
Small / On-device Models
Sound
Latest papersRecent research connected to this question, newest first.SCAPES: Semantically Conditioned Autoregressive Prior for Environmental SoundsThe source presents SCAPES, which synthesizes environmental sounds in the continuous latent space of a neural audio codec and evaluates semantic conditioning, interpolation, and long-term sample behavior. Evidence covers limited uncurated datasets and consumer hardware, but does not establish broad deployment or ecological-cost measurements.research paper · Sep 4, 2026
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