I think their engine works well with softer vocal like Baire here kinda eats a bit. But yea, most vocals suffers from having the generic feels to their voice. Idk, it might be an engine issue cus that specific in-the-nose feeling kinda noise is like very obvious in solid vocals
Omnivocal is now available!
"Omnivocal Basic" is a plugin included with #Cubase 16, powered by technology developed through VOCALOID.
For even more creative possibilities, "Omnivocal Pro" offers 10 voicebanks, Vocal Stack, and the full Omnivocal feature set.
Get Omnivocal Pro from the Steinberg Shop :
https://t.co/kJFlSNsXyN
Aaaand became e2e model
Andromeda is doing so fineee
Training takes long as hell tho and the model is still severely undertrained 😭
Art by wormwood_prod
Been brewing up a vocoder and architecture update. We are using auto-encoder and frequency domain neural vocoder instead.
Music: Mili
ustx: scoliosin
once again mixing sucks but well this is a quick test
Been brewing up a vocoder and architecture update. We are using auto-encoder and frequency domain neural vocoder instead.
Music: Mili
ustx: scoliosin
once again mixing sucks but well this is a quick test
Using nsf hifigan on a tiny update with crosslang TEST
Accent transferring implemented, but why would I want to hear Ritsu sing in English with strong Japanese accent lmao so im using English accent as a test
music & svp: FLAVOR FOLEY
mixing sucks but well this is a quick test
Like, if frequency domain discriminator generalizes into better scores than time domain, would that also means the same to the generator itself? Hmm. But the risk in phase incoherence is higher that's for sure
Im amazed in how frequency domain neural vocoder solidifies the frequency details way faster than time domain, but both it still take as long to refine into a similar fidelity to one another. Though, I don't even know if different domain has different fidelity ceilings
Been taking a look closer at synthv2 outputs, and I am amazed about how their residuals are so naturally non-coordinated. comparing it to nsf hifigan, they seems to be similar but different. Almost as if sv2 excitations are nonlinearly generated while nsf hifigan is shaped...
SLabeler has been slowly updated
Plan has changed, and I will only make one version instead of separate lite/full version.
I don't want to keep up with two of the same source code because one is already big enough.
https://t.co/1ctp004JeZ