# Tag Info

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The Cocktail Party Problem is a Blind Source Separation (BSS) problem. Given a linear mixture of signals: $$\boldsymbol{y} \left[ n \right] = A \boldsymbol{x} \left[ n \right]$$ We're trying to estimate the signal $\boldsymbol{x} \left[ n \right]$. The model can get even more complex with $A$ being time varying:  \boldsymbol{y} \left[ n \right] = A \...

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Couple of things: You really can't print to the console in a high-speed context, especially not in audio callback functions. That printing has side effects, and it's slower than you think, I promise. This alone breaks "real-timedness": You can never guarantee how fast your printing is (or isn't). Ahhhh! You're re-designing the filter for every ...

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Down-sampling is pretty straight forward in theory but difficult in practice. IN theory you just need to low-pass filter with a cutoff below half of the new sample rate and then you can just throw away the extra samples. In practice, the choice of filter involves a lot of trade offs that are highly dependent on the specific requirements of your application, ...

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Typically this requires a trade off between CPU efficiency and latency. Frame based signal processing incurs at least one frame of latency and it you are planning to play live through the effect, you need to keep this quite low otherwise it get's distracting. On the other hand, frame-based processing is way more efficient than sample by sample processing, ...

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Without re-hashing all of the maths from RBJs response, I made a crummy little plug in that did more/less what you are proposing. It had a stupid simple GUI with one slide for nominal amplitude and several more to control harmonic levels. It was OK, but not as useful as one would hope for audio work. The idea was that given a sinusoid with a nominal input ...

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For your known bug: Since your azimuth-elevation grid is uniformly distributed, finding the closest triangle containing the target direction is not difficult. Say the target direction is $(\varphi, \vartheta)$. Let $\varphi = [\varphi_1, \varphi_2, ..., \varphi_M]$ and $\vartheta=[\vartheta_1, \vartheta_2, ..., \vartheta_N]$ be ascending sorted arrays of ...

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This is a long post with a lot of info, I just and give some high level feedback Loose the 1.47 scale factor and just do everything on the unit sphere. If absolute distance/gain matters, just scale your whole HRIR set by 1.47/1. If you do a three point interpolation, the three points should form a triangle which encloses the point that you want. These are ...

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The answer is "sorta". Lot's of assumptions, though. This is related to that other question where you've been. This is about waveshaping of a single sinusoid (without harmonics) by performing a polynomial operation on a sinusoid having an amplitude of 1 and any frequency. It is memoryless, which will mean that the waveshaping operation is (at ...

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If you want the AI to relate to how we perceive sound, maybe something like a linear chirp from 20Hz-20kHz white noise in the same bandwidth a single sine wave at 1kHz (roughly our greatest sensitivity) a harmonic series from 55hz doubling up to 14.08kHz (all A notes to illustrate octaves) other harmonic series and/or progression to illustrate important ...

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Speech Source Separation (SSS) or Audio Source Separation (ASS) can be seen as a specialized version of source separation. I mention these expressions under which one can find additional works. One acceptation of the "Cocktail Party Problem" is the task of hearing/recovering one specific sound of interest in a complex environment (one-source ...

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Thanks to @Marcus Muller answer and comments in my question, I managed to solve th problem. As he pointed out: filtfilt is not the function you need. I saw that a hundred times: People use filtfilt because it has a name that reads a bit like it's the filtering operation they want, but it's not. You just need plain convolution. After fixing these ...

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In practice you would make sure that your filters don't have very large gains, at least not over a large frequency range. The filter you're using in the given example has a maximum gain of almost $26$ dB (at DC), and the gain is no less than $12$ dB for any frequency. I.e., you're applying a flat gain of $12$ dB, and on top of that you boost a relatively ...

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