jhetherly

3 ms·

1. 1.▲
   by jhetherly 9y ago

   Thanks for commenting and the suggestion! Indeed, the TED dataset has a lot of variability in terms of audio quality, etc. which, as you mentioned, with just 10 epochs of training is difficult to capture. I did try a larger network (up to 1
2. 2.▲
   by jhetherly 9y ago

   hey, author here Thanks for the feedback. "Something's not working properly here" - I disagree. The model will overtrain (i.e. perfectly reconstruct the original waveforms of a small training set), which indicates it's c
3. 3.▲
   by jhetherly 9y ago

   hey, author here Thanks for the feedback. "applying a similar technique in the frequency domain", "Maybe training an image reconstructor on the short term spectrogram" - This is what I originally thought to do. However,
4. 4.▲
   by jhetherly 9y ago

   hey, author here Thanks for the feedback. "the reconstructed audio sounded terrible" - I think this is referring to the amount of static noise in the reconstructed waveform. Indeed, the SNR clearly shows the reconstruction is slig