A supervised machine learning model that classifies environmental sounds (such as rain, thunder etc.) using Support Vector Machines and kernel-based feature transformations. Instead of using DNNs, this project leverages audio feature extraction (MFCCs, spectral features, chroma) and SVM’s mathematical rigor to recognize sound classes
svm hyperparameter-tuning non-linear-classification supervised-machine-learning kernel-tricks guarded-adaptive-kernel-selection
-
Updated
Nov 5, 2025 - Jupyter Notebook