I'm building a binary sound classifier using the ESC-50 dataset. I have taken one class, "dog bark", to be positive and the rest of the 49 classes to be negative. As the dataset is imbalanced I'm running into lot of training issues. I tried building a model but couldn't get a f1-score greater than 0.3.
I'm using mfcc and fft as features. I have tried used LR and SVM to train without much success. Can't use Deep learning models as it's a real-time system and can't have much delay.
How can I approach this problem?