Make: Volume 75

power of the signal at that frequency band.

Once the mel spectrograms were cropped

and resized to 256×256×3 inputs, they were fed

into the CNN. We found network training to be

somewhat unstable, likely due to the small and

noisy dataset. (For you machine learning fans,

the architecture contains about 144,000 trainable

parameters — for reference, the groundbreaking

AlexNet architecture has over 60 million

parameters! — and consists of descending

convolutional and max pooling layers with Leaky

ReLU activations for feature extraction and two

fully connected layers for classification.) We

wanted to keep the size as small as possible,

in order to ...