Myths of digital music
Lossy codecs (MP3 and others) can cope with modern electronic music, but cannot efficiently encode classical (academic), live and instrumental music.
The “irony of fate” here is that everything is actually the exact opposite. As you know, academic music in the vast majority of cases follows melodic and harmonic principles, as well as instrumental composition. From a mathematical point of view, this leads to a relatively simple harmonic composition of the music. So the predominance of consonances produces fewer side harmonics: for example, for the fifth (the interval in which the fundamental frequencies of two sounds differ by one and a half times), each second harmonic will be common for two sounds, for a fourth, where the frequencies differ by one third, every third, etc. Furthermore, the presence of fixed frequency ratios, due to the use of equal temperament, also simplifies the spectral composition of classical music.
The factors listed above lead to the fact that classical music is much easier to compress, mainly in a purely mathematical way. If you remember, mathematical compression works by removing redundancy (describing similar pieces of information using fewer bits), as well as predicting (so-called predictors predict the behavior of the signal, and then only the deviation of the actual signal from the predicted one is encoded; the more exactly they match, fewer bits are needed for encoding). In this case, relatively simple spectral composition and harmonicity lead to high redundancy, the removal of which provides a significant degree of compression, and a small number of bursts and noise components (which are random and unpredictable signals) leads to good predictability. mathematics the vast majority of information. Not to mention the relatively low average loudness of classic tracks and the frequent gaps of silence, which require virtually no information to encode. As a result, we can compress without loss, for example,
So, first of all, the fact is that the mathematical compression underlying lossless encoding is also one of the stages of lossy encoding (read Understanding MP3 encoding). And secondly, since lossy uses the Fourier transform (decomposition of the signal into harmonics), the simplicity of the spectral composition even makes the encoder’s job twice as easy. As a result, when comparing the original and encoded sample of classical music in a blind test, we are surprised to find that we cannot find any difference, even at a relatively low bit rate. And the funny thing is that when we start to completely lower the encoding bit rate, the first thing that detects the difference is the background noise in the recording.
As for electronic music, encoders have a hard time: noise components have minimal redundancy and, along with jerky jumps (some sawtooth pulses), are extremely unpredictable signals (for encoders that are “sharp “by natural sounds that behave completely differently), the direct and inverse Fourier transform with the rejection of individual harmonics by the psychoacoustic model inevitably produces pre and post echo effects, the audibility of which is not always easy to evaluate for the encoder … Add to this a high level of HF Components, and you get a lot of killer samples that even the most advanced encoders can’t handle at medium-low bit rates – oddly enough, it’s somewhere between the electronic music.
Also amusing are the opinions of “experienced listeners” and musicians, who, with a complete misunderstanding of the principles of lossy encoding, begin to claim that they hear how the instruments in music, after encoding, begin to falsify, the frequencies float, etc. perhaps it would still be true for detonating antediluvian cassette players, but in digital audio everything is exact: the frequency component remains or is discarded, there is simply no need to change the key.
Also: a person’s ear for music does not at all mean that they have good frequency hearing (for example, the ability to perceive frequencies> 16 kHz, which decreases with age) and does not make it easier for them to search for encoding artifacts at a loss. Since distortion has a very specific character and requires the expertise of blindly comparing lossy audio, you need to know
