7 citations · 8 across the 5 of their papers we have counts for
5 papers
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…
Urban Rhapsody: Large-scale exploration of urban soundscapes
Joao Rulff, Fabio Miranda, Maryam Hosseini +5
Noise is one of the primary quality-of-life issues in urban environments. In addition to annoyance, noise negatively impacts public health and educational performance. While low-co…
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…
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…
Weakly Supervised Source-Specific Sound Level Estimation in Noisy Soundscapes
Aurora Cramer, Mark Cartwright, Fatemeh Pishdadian +1
While the estimation of what sound sources are, when they occur, and from where they originate has been well-studied, the estimation of how loud these sound sources are has been of…