[D] 1D CNN on Waveforms and Spectrograms vs. 2D CNN Performance

It's counter-intuitive that most successful audio frameworks are using 2-dimensional convolutional neural networks (CNN), so I have tried to experiment while trying to train on [BirdCLEF-2024 on Kaggle](https://www.kaggle.com/competitions/birdclef-2024) using simple frameworks, and I have questions regarding learning:

1. When learning waveform input, why 1D CNN does not converge and even diverge immediately on validation split?
2. When training on spectrogram magnitude (stft -> abs -> log1p), why 1D CNN performs worse than 2D CNN?
3. While it seems that spectrogram …

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