papersSEP 12 04:00 UTC
Study compares methods to reduce catastrophic forgetting in sound event classification
A new arXiv paper examines ways to keep machine learning models from forgetting previously learned classes when trained incrementally on sound event classification. It evaluates architectural and regularization strategies using the FSD50K dataset and related benchmarks. The work is a research investigation rather than a released product.