61–70 of 76 posts
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Can you try it with Tom's Diner by Suzanne Vega? It's sung without any instruments, and an early version of MP3 reportedly was a disaster on that song.
Here you go: http://no.gd/vega2.wav It holds up ridiculously well considering the entire song compresses down to 25392 bytes.
OK, so... Would it be possible to do something similar for video?
Similar as in the same approach, or as in "apply neural networks to all the things"? Because if it's the former, this approach was very specifically tailored to human speech, taking into account how much it can compress/interpolate qualities like pitch and the spectral envelope. That's far too specific to apply to video. As for the latter, you'd have to perhaps feed Google Scholar the right incantations or ask someon…
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So can you do domain adaptation and get it to vocode my voice into Johnny Cash's? Larynx adaptation.
In theory, it wouldn't be too hard to implement with an neural network. In theory. In practice, the problem is figuring out how to do the training because I don't have 2 hours of your voice saying the same thing as the target voice and with perfect alignment. I suspect it's still possible, but it's not a simple thing either.
Earlier quoted context omitted.
Can you try it with Tom's Diner by Suzanne Vega? It's sung without any instruments, and an early version of MP3 reportedly was a disaster on that song.
Here you go: http://no.gd/vega2.wav It holds up ridiculously well considering the entire song compresses down to 25392 bytes.
I am curious how it sounds when there is a really active bassline and lead synth.
Just to put this in perspective, a traditional phone line encodes 56 Kb/s of data, which was believed to be the size channel to send the human voice with a reasonable quality. They are doing it in 1.6 Kb/s!
Aren't "traditional" aka POTS lines analog, and therefore not doing any encoding whatsoever?
G.711 (which is standard now for non-cellular call audio) is a step down, but Opus at 16Kbps sounds better to me than a classic, full analog system due to the lack of band cutoff & smarter encoding.
For comparison, your standard police/fire/medical digital radio in the US sends voice at 4.4Kb/s. So this is a approximately a third of that.
So maybe this line of work will mean more spectrum available in the future.
The examples sound excellent. Top (equal or better) of any text-to-speech synthesizer I've ever heard. I would love to start using it for audio books and for VoIP to save space and traffic as soon as possible. And a Linux-native text-to-speech synthesizer capable of producing speech of this quality is a thing I dream of (now the only option I know is booting to Windows and using Ivona voices)
3 Gflops, we are deep beyond diminishing returns here. Opus seems good enough.
Opus is awesome and covers a previously unmatched spectrum of use cases... but that isn't everything. Opus isn't good enough to be a replacement for AMBE for use over radio. Opus doesn't make it easier to make very high quality speech synthesis, etc. Opus loss robustness could be much better using tools from this toolbox-- and we're a long way from not wanting better performance in the face of packet loss.
The limiting factor for Opus's penetration has been compute, FEC is still rarely supported on VOIP deskphones due to this, ditto for handling multiple Opus calls at once.
For comparison, your standard police/fire/medical digital radio in the US sends voice at 4.4Kb/s. So this is a approximately a third of that.
3 Gflops, we are deep beyond diminishing returns here. Opus seems good enough.
Opus is awesome and covers a previously unmatched spectrum of use cases... but that isn't everything. Opus isn't good enough to be a replacement for AMBE for use over radio. Opus doesn't make it easier to make very high quality speech synthesis, etc. Opus loss robustness could be much better using tools from this toolbox-- and we're a long way from not wanting better performance in the face of packet loss.