manadream wrote: ↑
Tue Aug 25, 2020 7:50 pm
Okay, thanks for that clarification. Though I am confused by no resampling being the lowest quality, it doesn't seem that way to me in terms of sound quality. No interpolation preserves the sample quality and does not make it sound flat or altered in any way.
It seems you keep confusing resampling with interpolation.
is the lowest quality interpolation method (there's actually no such thing, see below).
preserves the original sample's quality, but that can only happen when the original sound's sample rate matches the sound card's output frequency.
Remember that typical sound cards have output frequencies of 44100 or 48000 Hz, therefore to preserve this quality, all samples must have been sampled at that frequency and played without any frequency change, which means you can't get different notes from the same sample, and that you have to use a different set of samples depending on the sound card's output frequency. It's possible to have a module consisting of one sample per note, and all samples at the same frequency, and play a different sample whenever you want to change the note, and then have one module per typical output frequency, but it would take much more space and time to prepare. In this scenario, interpolation would be useless, as it would do nothing by definition (or it can even alter the sound if it isn't real interpolation).
In order to generate different notes, a tracker must be able to play each of the samples at many different frequencies, and since the audio card has a fixed output frequency, the only way to do this is by resampling, and to do that, in almost every case you need to interpolate (the only exception is if you need to downsample to a frequency that is the original sample frequency divided by an integer, which in practice almost never happens).
"No interpolation" is actually a misnomer. Interpolation, by definition, consists of determining values between existing samples, and is needed when you resample a sound such that some of the new samples lie between two of the samples of the original sound, which will happen in all cases except the rare one mentioned above. The interpolation algorithm that we usually call "no interpolation" is actually "left neighbour" interpolation (or it can refer to another one which is rarer in audio, but more common in imaging: "nearest neighbour").
It's similar to the case of images. Say you have an original "analogue" image (not an image file, but a real life scene) and you want to convert it to a bitmap by taking a photo with a digital camera (let's assume it's a B/W photo for the analogy to be closer). You need to choose a resolution (equivalent to the sampling frequency in audio). Then the camera converts it by approximately averaging the light in each small square pixel and turning it into one sample value for that pixel. This bitmap is our original sample. Say it's a 512x288 image. In our audio equivalent, for this example it will be a 16KHz sound.
But LCD monitors (sound cards) have a fixed resolution (output frequency). You can't draw that 512x288 image (16KHz sound) at full size in a 1920x1080 monitor (48KHz card) without scaling (resampling). At best you can show (play) it at its original scale (sampling rate) so that each image pixel is in one LCD pixel (so that each audio sample corresponds to one sound card's output sample). Here the analogy breaks a bit because if you display the image at 512x288, it's still recognizable, but if you play the 16KHz sound at 48KHz, it will sound extremely high-pitched. But please bear with me.
But in order to make collages (music notes) you need to be able to place the image at different sizes (play the sound at different rates), and unless you took one picture for each resolution (one audio for each note) that you're going to use, you're going to need an interpolation algorithm in order to scale (resample) the image (sound).
In terms of preserving the original image's (sound's) quality, the nearest neighbour method is pretty bad. It has visible (audible) squares (artifacts). Remember that we're not talking about pixel art, but real world images. In most cases, a better interpolation algorithm can help making the image (sound) be more pleasant to look at (hear). Still, if your original image (sample) has a poor resolution (sampling rate), it's going to look (sound) bad; probably blurred (muffled).