Thanks Ricardo,
The demo was interesting, some high frequency reconstruction. I wonder
if they mean "kHz" in the article rather than "kbps) when they referred
to down sampling. The banner at the bottom made reading the article
really annoying.
As it happens I playing with some similar ideas right now. Speech does
have some correlation across the frequency axis. So if you know one
part of the spectrum of a frame of speech, you also have some
information about the other part.
This correlation can be found using neural nets, or vector quantisation.
Or we can explicitly remove the correlation using techniques like a
DCT, leaving us much less information to sen dover the channel.
Cheers,
David
On 24/06/17 08:41, Ricardo Andere de Mello wrote:
Hi,
Recently I have been working with deep learning, but mainly focused in
image recognition.
I found one article related to audio, and I thought you would find it
interesting:
https://blog.insightdatascience.com/using-deep-learning-to-reconstruct-high-resolution-audio-29deee8b7ccd
I was wondering if it would be possible to use codec2 frames as inputs
for training.
[]s, Ricardo Mello
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