- Set sample rate of all the wav files to 20kHz
- All the clips set to 100k samples by padding and croping clips
- Merge all the 10 classes into one folder and prepare 5 stratified folds and get a NPZ file as the resultant dataset
- Classes are 0 indexed
- chainsaw: 0
- clock_tick: 1
- crackling_fire: 2
- crying_baby: 3
- dog: 4
- helicopter: 5
- rain: 6
- rooster: 7
- sea_waves: 8
- sneezing: 9
- create a folder named "data" and include the folders of 10 classes into that
- you can change the sample rate and the number of samples accordingly
- create a python env, install the requiered libraries and run the notebook "preprocess.ipynb"
- NPZ file will be saved in the data folder