7 citations · 8 across the 5 of their papers we have counts for
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cs.SD2023★ 1 cited
A General Framework for Learning Procedural Audio Models of Environmental Sounds
Danzel Serrano, Mark Cartwright
This paper introduces the Procedural (audio) Variational autoEncoder (ProVE) framework as a general approach to learning Procedural Audio PA models of environmental sounds with an…
cs.SD2022
A Study on Robustness to Perturbations for Representations of Environmental Sound
Sangeeta Srivastava, Ho-Hsiang Wu, Joao Rulff +5
Audio applications involving environmental sound analysis increasingly use general-purpose audio representations, also known as embeddings, for transfer learning. Recently, Holisti…
cs.SD2021
Who calls the shots? Rethinking Few-Shot Learning for Audio
Yu Wang, Nicholas J. Bryan, Justin Salamon +2
Few-shot learning aims to train models that can recognize novel classes given just a handful of labeled examples, known as the support set. While the field has seen notable advance…