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Don't you just love teh sky? (´ー`)

there are gif comments on youtube now

*chop loli*

Those of you who have been browsing, lurking, and posting on various altchans, do you have any interesting stories to share?

lil nigra wanna be president and shiet

Note: The image is just a generic of Linear Predictive Coding I found, because new threads require an image, it doesn't have anything to with this proposal specifically, besides it being related to LPC in general.

In previous articles, I have discussed sources of error within the Wide-Band Harmonic Sinusoidal Modeling framework. Although I have not implemented most of the proposed improvements yet, I have derived closed-form solutions for several sources of error and have also provided theoretic justifications for the proposed solutions. Notably though, one source of error - named in the original paper - has still gone unaddressed.

This is the intrinsic error that results from the actual vocal tract filter varying continuously, whereas in the model we have assumed that it remains constant over given intervals. In the original WBHSM framework, these intervals were single pitch periods that were presumed to correspond to a sum of an infinite number of identical voice pulses. In my last proposed improvement on WBHSM, which I called Radiated Voice Pulse Modeling, I proposed solutions, in the form of corrective terms, to the errors that resulted from actual voice pulses not all being identical. However, each pulse was stilled modeled as having a constant vocal tract filter. Actually, theoretically it got worse since we were now considering the pulses whole radiated duration (up to a reasonable cut off point) as the pulse instead of a single period, although in practice the added error would not be significant because the proposed implementation only adds error terms that are in proportion to the differences between voice pulses.

This problem would seem unresolvable within WBHSM framework, since it is based on frequency-domain modeling, which is based on linear time-invariant filters with defined z-transfer function. Since the actual vocal tract filter varies continuously, it is not time-invariant and thus does not have a z-transfer function nor a frequency response. Thus my proposed solution involves hybridizing the WBHSM technique with another technique that can model time-variant filters, namely Linear Predictive Coding.

Linear Predictive Coding has a well-known deficiency, which is that it is an all-pole filter that does not model z-plane zeros. This would seem to negate much of the benefit of using it, but this is actually not true. Disregarding the non-linear aspect for a moment, if we think of the z-transfer function of an infinite impulse response filter, w

Comment too long, view post No.197239 to see the full comment.

In this thread, let's make abstract art and try to guess what it is or what it means

meanwhile in krakow

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sports are important!

There's been a lot of mistakes I've known about for a while but haven't bothered to publicly mention yet. I thought I'd finally do that.
https://queuesevenm.wordpress.com/2026/10/18/some-overdue-corrections/
Also, another thing I said that was wrong originally is which processing techniques VOCALOID 1 and VOCALOID 2 use. The correct answer is V1 uses Spectral Modeling Synthesis, while V2 uses Spectral Peak Processing/Scaling/Phase-locked Vocoder.

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