only the silliest will survive

>>13272 sigh... its like you can still hear his voice... its so tragic that syrno passed away so young, but i guess thats what happens when you mix drinking and driving.....

>>13278 Drinking and driving is safe if you're skilled enough

>>13272 Syrno will replace the current captcha for mathematical calculations and will change the site name for "HeyKaren"... please Syrno, dont complicate thing for us

>>13268 Wouldn't you like to know.

>>13200 Uatta faku

>>13115 With this post i dispel the bad fortune

I made the right choice.

will beginner's luck work??

>>13208 Jordi Bonada* I need to sleep

I have implemented an improvement to the laryngograph onset detection procedure. In typical laryngograph signals, like most signals, there is high-frequency noise. However, in addition to this high-frequency noise, there is also an abundance of low-frequency noise, usually much more than the high-frequency noise. This is due shifting of the neck and laryngograph. The standard DSP solution to this problem would be to use a highpass filter. However, the frequency of this noise, and thus the required transition band, are so low that it would render a standard single-stage FIR highpass filter impractical. The complete procedure I have implemented is follows: 1. The signal is lowpass-filtered (to filter out the high-frequency noise). 2. Peaks (which correspond to glottal closure instants) are detected and interpolated using quadratic interpolation. The topographical prominence is also calculated for each peak, and peaks below a minimum prominence are discarded. 3. In between each adjacent pair of peaks, the minimum valley is found (also using quadratic interpolation). 4. An envelope is created using the natural cubic spline algorithm from this set of minimum valleys. 5. This envelope is subtracted from the original signal. 6. The signal is filtered again, replacing the old filtered signal. 7. Peaks are detected again, replacing the old set of peaks. 8. These peaks are grouped into regions using two heuristics: distance between subsequent peaks and change in subsequent distances. 9. Regions with only one peak are discarded. Another approach would be to use two-stage downsampling. Then, it could be further lowpass-filtered to obtain fine-control (the new sample rate is chosen to be efficient, not necessarily precisely what is desired). These values could then be used in the same interpolation procedure; alternatively, they can be upsampled back to the original sampling rate (also using a two-stage process for efficiency reasons) and this signal subtracted from the laryngograph signal. This approach is more correct in theory. On the other hand, this assumes a perfectly periodic signal. In reality, the laryngograph pulses vary. Furthermore, they are most definitely not period around the start and end of voiced regions. This aperiodicity will distort any filtering operation. On the other hand, the valleys in between pulse generally vary much less than the signal overall. Two stage downsampling is also less efficient than the spline approach.

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, we can appreciate that it can be decomposed into two separate filters: An finite impulse response filter that models the zero, and an all-pole infinite response filter that models the poles. From this angle, inverse filtering just the poles would leave of us with the voice source convolved with an FIR filter that corresponds to the zeros. Since the number of taps in that filter is directly related to the number of zeros, its size can be presumed to be small and thus the convoluted pulses can also be reasonably presumed to not overlap. Furthermore, an all-pole filter has a practical benefit in the deconvolution process, which is that it is not susceptible to numerical stability issues, at least within floating-point arithmetic. One important issue is where the vocal tract filter's estimation is to be sourced from. There are basically two options: Either within LPC or within WBHSM. In the latter case, there is a problem. The current vocal tract model I am using is called Excitation plus Resonance. This model models each resonance as a parallel component of the vocal tract filter. On the other hand, LPC presumes a cascade configuration. One may think to simply modify the EpR model to be cascade instead, but this is not as trivial as it may seem. The procedure I have used for resonance estimation, which I have called Formant Region Iterative Refinement (the first iteration of which was detailed here: https://queuesevenm.wordpress.com/2026/06/02/recreating-the-excitation-plus-resonance-model/), is fundamentally based around adjusting each resonance according to its local surroundings and that inter-resonance effects are minimal. A cascade configuration breaks the second requirement. (continued in next post)

(continued from previous post) One option would be to somehow modify the LPC inverse filtering process to be amenable to a parameter configuration instead. However, I am not sure how to do this, or whether it is even possible (perhaps a good place to start would be to frame the problem as a matrix equation?). On the other hand, another option would be to create a cascade filter from the estimated parallel filter. This could be done by first starting with just the first resonance. This is the same in both cases. Then we go on to add the second one. Before adding it, we calculate the current value in the cascade filter at the next resonance's center frequency, we then scale its amplitude by the reciprocal of this value. This new filter will not be exactly the same, but it should be reasonably close. Actually, it may be a better model of the vocal tract. Perhaps also the FRIR algorithm could be used to refine it, even in the cascade case, since it should have a very low error? The final procedure then, would be to run one iteration of the WBHSM algorithm, to estimate the EpR parameters. Then, for each instant an EpR model has been estimated, only the poles are extracted and are then converted to a cascade filter. Next, the inverse filtering is performed. For each inverse filtering frame (which can be as small as a single frame), the closest vocal tract filter estimates are interpolated using, for example, linear or spline interpolation. Next, the z-transfer function denominator of the resultant filter is expanded using the standard procedure to obtain the LPC coefficient, which are finally used to do the inverse filtering itself. The final step is the second pass of WBHSM, over the inversecfiltered signal. Since it has been inverse filtered, there should be no interference between voice pulses. An additional potential benefit is the harmonic envelope no longer contains resonances, which may improve the estimation of the source curve and zeros, although the same effect could also be achieved in the traditional EpR estimation by using two passes. Finally, a combined EpR model is created from the resonance plus the source and residual model obtained in the last step. This procedure makes one significant presumption, which is that most of the error of WBHSM is concentrated in the non-resonance part of the EpR model. This would seem to be a reasonable assumption to make, given that EpR is fitted using multiple harmonics, and that it could furthermore be filtered across multiple frame using techniques such as lowpass filtering, moving averages, or exponential moving averages. However, I do not yet have empirical evidence for this. One possible case wherein the presumption would not hold would be if the error changes slowly over frequency, for example. Actually, a type of error with precisely this fingerprint does exist; it results from the fundamental frequency changing. However, I have already proposed a solution to it, within the RVPM framework: https://listserv.cuit.columbia.edu/scripts/wa.exe?A2=MUSIC-DSP;31999a11.2608A&S=

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.

No. Maybe. Fuck you!

w-what's going to happen hikarin?

>>13259 Not sure i will be able to post ever again with those tohou captchas

>>13235

>>13234 fighting hikarin! have you returned to continue the Fight?

You candy asses aint fighting shit, lil bitches!

>candy ass Does it mean it's sweet?

Yes, why not have a taste?

awww, how cute!

good post

>>13240 Thank you

But the board you linked to is full of no-no topics

>>13243 Just ignore the roodey p**s or mock them

it's bad

>>12225 Whats up, the sky dummy, a fly nyagan his mouth kept running, his mother's crying, cuz hikari stunned him and left was nothing

llms mog me too hard

What

i feel useless cuz i'm dum while the bot actually can find the necessary info for me and also help me immensely with troubleshooting

>>13188 hikarin

>>13188 >>13202 Gay.

>>13204 so long as you tell yourself it's not...

>>13206 Keep telling yourself that twink bitch!

I liked this https://en.wikipedia.org/wiki/Lemonsoda and would drink it every few days but it got old. The cans have this issue with particles that i couldnt quite identify settling at the bottom so when i tried it again it was kind of gross

I like da bepis made with real sugar

>>13094 I stopped drinking cokes years ago but Barq's was always my favorite.

Delicious.

>>13094 im sippin on some A 'n' dubya

>>13158 I can't play vrchat, the people I've encountered are insufferable

>>13159 Yeaaa hikarin, that seems to be the most common experience for newcomers From my understanding of things, the best way there is to play the game, is by doing a bit of research on the small communities that gather in private worlds to hang out; I remember there was this one that had tea parties every wednesday or something, and it looked super comfy and friendly Going into public lobby's is definitely not a good idea at alL!!

>>13160 how did pippa get twisted 360° inside the tank

I'm so unbelievably horny.

>>13190 jerk off to flash games