This paper discusses piece-wise polynomial interpolators used in audio resampling
and presents new low-order designs that are optimized for high-quality resampling
of oversampled audio. Source code and useful tables for using the interpolators are
included

Here is a paper on more or less that exact topic:

Quote

This paper discusses piece-wise polynomial interpolators used in audio resampling
and presents new low-order designs that are optimized for high-quality resampling
of oversampled audio. Source code and useful tables for using the interpolators are
included

https://yehar.com/blog/wp-content/uploads/2009/08/deip.pdf

You can see each interpolator compared to linear and pick the one you want. 

Quote from: saratoga on 2024-09-11 16:31:20

Here is a paper on more or less that exact topic:

Quote

This paper discusses piece-wise polynomial interpolators used in audio resampling
and presents new low-order designs that are optimized for high-quality resampling
of oversampled audio. Source code and useful tables for using the interpolators are
included

https://yehar.com/blog/wp-content/uploads/2009/08/deip.pdf

You can see each interpolator compared to linear and pick the one you want. 

Thanks, but I could not see anything brighter than linear interpolation.

Quote from: Klymins on 2024-09-11 21:48:42

Quote from: saratoga on 2024-09-11 16:31:20

Here is a paper on more or less that exact topic:

Quote

This paper discusses piece-wise polynomial interpolators used in audio resampling
and presents new low-order designs that are optimized for high-quality resampling
of oversampled audio. Source code and useful tables for using the interpolators are
included

https://yehar.com/blog/wp-content/uploads/2009/08/deip.pdf

You can see each interpolator compared to linear and pick the one you want. 

Thanks, but I could not see anything brighter than linear interpolation.

What does that mean?

Hello. As I already said in other topics, I think linear interpolation greatly improves the sound of lower sampling rates (for example 11025Hz). But, linear interpolation is not perfect. On some sounds, I can feel the lack of the ideal brightness, and I want to have another option with higher brightness. Zero-order hold is brighter, but because it's reflections of low frequencies are very loud, it sounds bad to my ears in most cases. So, I want to improve linear interpolation by increasing the trebles. I made it sound better with TDR Nova (10kHz, 15dB, 0.6q, 3.option sounds good for 11025Hz), but I want a perfect algorithm. Here's my wishes:

I can certainly understand that if your source is

Quote from: Klymins on 2024-09-11 13:55:15

Hello. As I already said in other topics, I think linear interpolation greatly improves the sound of lower sampling rates (for example 11025Hz). But, linear interpolation is not perfect. On some sounds, I can feel the lack of the ideal brightness, and I want to have another option with higher brightness. Zero-order hold is brighter, but because it's reflections of low frequencies are very loud, it sounds bad to my ears in most cases. So, I want to improve linear interpolation by increasing the trebles. I made it sound better with TDR Nova (10kHz, 15dB, 0.6q, 3.option sounds good for 11025Hz), but I want a perfect algorithm. Here's my wishes:

You EQ it up at 10 kHz and then sample at 11025 killing everyting above 5.5k - and complain that it has little treble?

Suggestion: have a look into perceptual noise substitution. ( https://www.audiolabs-erlangen.de/content/resources/aesCodingTutorial/pns.html , https://ccrma.stanford.edu/~kapilkm/422/Audio%20Compression%20using%20Entropy%20Coding%20and%20PNS-1.pdf )
In principle you can code up something that does the following:
 * Scan the original audio. Get an idea of the levels of the frequency bands.
 * Upon encoding, replace everything above 5.5 kHz with "put noise at <volume> instead". AAC (and IIRC, Musepack in the "radio" settings) can generate that "for cheap" in terms of storage.
 * ... and of course that is distortion, but it preserves part of the original signal (the frequency response). But once you are doing that, you can boost the 10 kHz range.

(Or, use an EQ upon playback?)

Quote from: Porcus on 2024-09-12 10:01:14

I can certainly understand that if your source is

Quote from: Klymins on 2024-09-11 13:55:15

Hello. As I already said in other topics, I think linear interpolation greatly improves the sound of lower sampling rates (for example 11025Hz). But, linear interpolation is not perfect. On some sounds, I can feel the lack of the ideal brightness, and I want to have another option with higher brightness. Zero-order hold is brighter, but because it's reflections of low frequencies are very loud, it sounds bad to my ears in most cases. So, I want to improve linear interpolation by increasing the trebles. I made it sound better with TDR Nova (10kHz, 15dB, 0.6q, 3.option sounds good for 11025Hz), but I want a perfect algorithm. Here's my wishes:

You EQ it up at 10 kHz and then sample at 11025 killing everyting above 5.5k - and complain that it has little treble?

Suggestion: have a look into perceptual noise substitution. ( https://www.audiolabs-erlangen.de/content/resources/aesCodingTutorial/pns.html , https://ccrma.stanford.edu/~kapilkm/422/Audio%20Compression%20using%20Entropy%20Coding%20and%20PNS-1.pdf )
In principle you can code up something that does the following:
 * Scan the original audio. Get an idea of the levels of the frequency bands.
 * Upon encoding, replace everything above 5.5 kHz with "put noise at <volume> instead". AAC (and IIRC, Musepack in the "radio" settings) can generate that "for cheap" in terms of storage.
 * ... and of course that is distortion, but it preserves part of the original signal (the frequency response). But once you are doing that, you can boost the 10 kHz range.

(Or, use an EQ upon playback?)

I EQ it up at 10kHz after sampling at 11025Hz, so there's lots of sounds above 5512.5Hz.

Quote from: Klymins on 2024-09-12 11:27:07

Quote from: Porcus on 2024-09-12 10:01:14

I can certainly understand that if your source is

Quote from: Klymins on 2024-09-11 13:55:15

Hello. As I already said in other topics, I think linear interpolation greatly improves the sound of lower sampling rates (for example 11025Hz). But, linear interpolation is not perfect. On some sounds, I can feel the lack of the ideal brightness, and I want to have another option with higher brightness. Zero-order hold is brighter, but because it's reflections of low frequencies are very loud, it sounds bad to my ears in most cases. So, I want to improve linear interpolation by increasing the trebles. I made it sound better with TDR Nova (10kHz, 15dB, 0.6q, 3.option sounds good for 11025Hz), but I want a perfect algorithm. Here's my wishes:

You EQ it up at 10 kHz and then sample at 11025 killing everyting above 5.5k - and complain that it has little treble?

Suggestion: have a look into perceptual noise substitution. ( https://www.audiolabs-erlangen.de/content/resources/aesCodingTutorial/pns.html , https://ccrma.stanford.edu/~kapilkm/422/Audio%20Compression%20using%20Entropy%20Coding%20and%20PNS-1.pdf )
In principle you can code up something that does the following:
 * Scan the original audio. Get an idea of the levels of the frequency bands.
 * Upon encoding, replace everything above 5.5 kHz with "put noise at <volume> instead". AAC (and IIRC, Musepack in the "radio" settings) can generate that "for cheap" in terms of storage.
 * ... and of course that is distortion, but it preserves part of the original signal (the frequency response). But once you are doing that, you can boost the 10 kHz range.

(Or, use an EQ upon playback?)

I EQ it up at 10kHz after sampling at 11025Hz, so there's lots of sounds above 5512.5Hz.

Do you mean EQ it after upsampling from 11025 to something higher?  You could not apply 10k EQ to an 11025 Hz signal for obvious reasons. 

Here is a paper on more or less that exact topic:

Quote

This paper discusses piece-wise polynomial interpolators used in audio resampling
and presents new low-order designs that are optimized for high-quality resampling
of oversampled audio. Source code and useful tables for using the interpolators are
included

https://yehar.com/blog/wp-content/uploads/2009/08/deip.pdf

You can see each interpolator compared to linear and pick the one you want. 

Quote from: saratoga on 2024-09-11 16:31:20

Here is a paper on more or less that exact topic:

Quote

This paper discusses piece-wise polynomial interpolators used in audio resampling
and presents new low-order designs that are optimized for high-quality resampling
of oversampled audio. Source code and useful tables for using the interpolators are
included

https://yehar.com/blog/wp-content/uploads/2009/08/deip.pdf

You can see each interpolator compared to linear and pick the one you want. 

I want to try some of the interpolators written in this document, how can I do that (MultiResampler only supports ZOH, linear, cubic, and sinc)?

The paper gives the code for each interpolator (see section 6), but you have to be able to program to use it yourself. 

Seems like you has fallen down to the placebo perception self lying for listening a bunch of aliased signals.
I recommend you to use (if you use foobar2000) a component that ads something living to the high frequencies content, that is the component called Noise sharpening (foo_dsp_delta).
Regards.

Am I confused? The resamplers in saratoga's link seem to target transparency. Klymins' goal is to introduce noise.

@Klymins I'll point out that linear interpolation can also smear transits and cause things to become slightly muffled.  32 KHz to 44.1 KHz for example.  The point is that kind of interpolation is crap as it adds crap that's not even there to begin with.  It's used because it tends to be quite fast.  What you're hearing with better re-sampling is what the audio actually sounds like with nothing added, which is going to be muffled because the sampling rate is not enough in that case.  DirectX for example uses linear interpolation because it is very fast and that's important for games (the fact is it needs to be quite fast and the lowest possible latency) not because it provides a better audio experience for lower sampling rates.  Developers want to save space and so one of the ways they do it is to drop the quality of the recording used and many developers will exploit the shortcomings of any platform to their advantage even if it is technically wrong to do so.  These people know exactly what they're doing.  You'd be quite surprised how developers will use various kind of tricks and techniques to get a game to do what they want it to do based on what a platform allows or is capable of.

You like noise and distortion and that's it.  There's nothing to improve here.  You can play around with filters and very low quality interpolation all day long everyday for the rest of your life.  The real improvement came in not actually adding crap that wasn't there (or that muffled sound you don't like).

Regardless I think you are going about this the wrong way.  Upsample first using accurate resampler to preserve maximum high frequency information, then once everything is safely at the higher sampling rate look into spectral extension DSPs.  This will work much better.

I recommend you to use (if you use foobar2000) a component that ads something living to the high frequencies content

In psychology, an idée fixe is a preoccupation of mind believed to be firmly resistant to any attempt to modify it, a fixation. The name originates from the French idée [i.de], "idea" and fixe [fiks], "fixed."