Making noise: success!

That title is very accurate – I’ve now succeeding in making pretty pure noise, although it does seem to have a liiitle bit of pulsation in it.

[UPDATE: Alex pointed out that doing mysequence.astype(‘int16’) did not actually modify the array in place, so my audio wasn’t really encoded properly. Proper version below]

I started using bokeh to do live-plotting of learning curves and thought I was saving them as pngs, but it turns out I was not, so I only have the first couple batches of the latest experiment I ran to put here for now:

[UPDATE: Here’s the training loss for the model described below]

train_loss

But the good news is I’m now truly set up with Blocks, Fuel, and bokeh to run and log multiple experiments.

I’m currently using a 2-layer LSTM, with the following hyperparameters:

  • frame length: 4000 samples
  • sequence length: 50 frames
  • batch size: 128
  • hidden layer size: 200
  • learning rate: 0.002
  • epochs: 30

I’m also using gradient clipping. Most of these decisions are fairly arbitrary at the moment – I’ve just been working on getting plots and audio made so that now I can look at the details of my experiments.

The model trains and everything, but the audio generated has a lot of noise in it and does not sound very much like the vocal data it was trained on – I’m going to try a better overlapping to smooth out the transitions.

 

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