This is a musical instrument classifier that works with two different network architectures:
- Convolutional Neural Network
- Transformer
The report over this project can be found here.
The dataset used is the Medley Solos DB. The instruments within the recordings are:
- Clarinet
- Distorted Electric Guitar
- Female Singer
- Flute
- Piano
- Tenor Saxophone
- Trumpet
- Violin
During training, a random slice of two seconds are used to have a more diverse training set. Once training is complete, a file should be saved under ./trained_models/.
To train, run:
python3 train.py --model cnn --epochs 15 --lr 1e-4
python3 train.py --model transformer --epochs 15 --lr 1e-4
where --lr is the learning rate (1e-4 was found to be the best) and --epochs is the number of epochs.
Once training is completed, the loss over training epochs should be displayed. Also, a confusion matrix from the test set will be displayed along with the accuracy report printed to console.