When I saw the images of the converted audio files my first thought was, that there is not much information on it → a lot of black space.
Nice work! It makes sense that the Short-time Fourier Transform and the rescaling work wonders. I’ll definitely try your preprocessing steps in my next experiments.
Is there any information about xresnet? I’d like to know what’s self attention and MISH activations ;).
The xresnet architecture is mostly based off modifications in the Bag of Tricks paper. Self-attention is also really useful across all tasks in modern deep learning (e.g., paper). Mish is an activation function written by @Diganta (see paper). A lot of this is encapsulated in a post by @LessW2020 regarding another Fastai competition.
(what’s the best way to paste code here?)
Your code blocks are perfectly fine! Note that you can put ```python in the first row do get syntax highlighting/coloring.
def get_x(path):
rate = 24414
[...]