Chapter 5: Audio Generation with NSynth and GANSynth

1. You have to handle 16,000 samples per second (at least) and keep track of the general structure at a bigger time scale.
2. NSynth is a WaveNet-style autoencoder that learns its own temporal embedding, making it possible to capture long term structure, and providing access to a useful hidden space.
3. The colors in the rainbowgram are the 16 dimensions of the temporal embedding.
4. Check the timestretch method in the audio_utils.py file in the chapter's code.

5. GANSynth uses upsampling convolutions, making the training and generation processing in parallel possible for the entire audio sample.

6. You need to sample the random normal distribution using np.random.normal(size=[10, 256]), where 10 is the number of sampled instruments, and 256 is the size of the latent vector (given by the latent_vector_size configuration).

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