Hi Community!
I’m seeing promising results on a 10 class audio classification task.
I am getting 76.3% accuracy with fastai and basically no effort, so that’s really cool! However, according to the publications listed on the dataset’s website, the top accuracy is 79%.
My goal is to surpass that by next weeks class, so I’m asking you guys for suggestions on what the most fruitful avenue might be:
- tune hyperparameters
- add audio specific data augmentation (obviously the common transformations don’t help with spectrograms)
- create better spectrograms which could be easier to classify
Here is my notebook.
thanks @jeremy for making this course so fun!