Tag: was ist audio compression

Digital audio compression

The concept of loudness is close and understandable not only for a musician, but also for people who are not associated with music. The relationship between the volume of the parts of a piece and the volume of the instruments that are playing simultaneously is called the dynamic range. One of the main tools producers and musicians use to influence dynamic range is the compressor.

Although the compressor works with a known phenomenon, loudness, in most cases its use occurs spontaneously, randomly, without understanding the essence of what is happening. You can know the general principle of the compressor and the purpose of each handle, but this does not eliminate the stupor at the first experience.

Why do you need a compressor?

The main purpose of the compressor is to automatically change the signal level. It works roughly the same as if you kept your hand constantly on the volume fader, turning it up and down. The difference is that a compressor can react very quickly to changes, much faster and more accurately than a human.

Up to this point, the word compressor meant a whole class of dynamic devices. Using the same basic principles as a conventional compressor, various instruments work for different purposes: limiters, expanders, gates, etc. They are united by working with the volume of individual sounds or the mix as a whole.

The classic compressor is controversial by its very name. Everyone knows that he makes the loudest sound. But the name comes from compress, which means “compression”, and if you ask any sound engineer what a compressor does, you’ll hear the answer: “squash the signal.” The compressor reduces the amplitude of the dynamic bursts, makes them quieter. So what is the main purpose of the compressor: to make it quieter or louder? The answer is both at the same time.

Let’s take an example of voice recording. Very often, in the process of singing, syllables or sounds of different volume are heard. If the singer does not control the dynamics of his performance very well, then such differences create problems for the sound engineer and negatively affect the final result of the work. Silent syllables disappear into the mix, text becomes difficult to distinguish, and if you adjust the volume for a quiet area, in other places the voice begins to “stand out.”

This is where the compressor comes in. It allows you to suppress strong bursts, equalize them with silent fragments. Now you can turn up the volume of the track without fear of some syllables sticking out. So the compressor makes the sound lower and higher at the same time. Three images show the stages of working with sound: a source with large peaks (a), a compressed signal (b) and an increase in the volume level of the entire file (c).

It is especially important to apply compression when recording in a digital environment, when we are forced to adhere to a maximum level of 0 dB, because exceeding this threshold leads to clips and distortion. When clips appear, we lower the preamp level, which means we lower the volume of not only bursts, but quiet areas as well, leading to signal degradation due to quantization and aliasing noise.

The compressor, positioned between the preamp and the digital recording system, operates only on the loudest bursts, reducing their volume and ensuring a smooth soundtrack. Thanks to this, we have the opportunity not to reduce the overall volume of the recorded signal and to maintain the sound quality.

Unfortunately, many modern musicians, without going into the technical characteristics of the compressor, use it everywhere, believing that with its help you can “stretch” any sound in the mix. Also, compressors are often included on the road in extreme conditions. They are only used by experienced sound engineers when there is a real need.

The compressor helps avoid recording problems. The most common causes of problems can be the following:

Non-professionalism of the interpreter (dynamic unevenness).
Mismatched path (bad, mismatched, or inadequate microphones, preamps).
Disadvantages of the digital environment (limited to 0 dB).
Uncomfortable conditions for the singer (small and stuffy room, poor monitoring).
Low qualification of a recording engineer.
If a performer has a voice and can sing into a microphone, and a recording engineer knows her job well and knows how to properly position microphones and set up equipment, a compressor may not be required at all. But this is the ideal situation.

Digital audio compression

Audio data compression is a real problem today. There are two reasons for the need to compress audio data: memory savings when storing audio information, low bandwidth of remote digital information transmission channels. Compression effectively solves the two problems above. Data compression is an algorithmic transformation of data performed to reduce its volume.

It is used for a more rational use of data storage and transmission devices. Compression is based on eliminating the redundancy contained in the original data. To guarantee the parameters necessary for the transmission of voice signals (music) over modern low-speed digital communication channels and to guarantee the specified noise immunity, it is necessary to use highly efficient data compression algorithms. The transmission channel is characterized by a concept such as the capacity of the channel: And the signal – by the volume (signal): …

Both of the above features include dynamic range D, channel width (signal spectrum), and transit time T. Digital audio compressors are used to reduce dynamic range. To improve spectral efficiency, digital filters are used to limit the spectrum of the encoder output signal (according to Nyquist criteria). Among other things, encoders based on the principles of elimination of redundancy (Huffman codes) are used to guarantee a certain information transmission speed. The essence of which is as follows: codes based on the principle of assigning more probable values ​​of the amplitudes of the codewords of shorter length than the improbable ones.

Let’s consider how the types of redundancy described above are eliminated.
Structure of a lossy audio compression encoder The original digital audio signal is divided into frequency subbands and time-segmented into a time-frequency segmentation block. The length of the encoded sample depends on the shape of the temporal function of the audio signal. In the absence of sharp peaks in amplitude, a long sample is used, which provides high-frequency resolution. In the case of abrupt changes in signal amplitude, the length of the encoded sample decreases dramatically, giving a higher time resolution. The decision to change the length of the coded sample is made by the psychoacoustic analysis unit, calculating the value of the psychoacoustic entropy of the signal.
After segmentation, the frequency subband signals are normalized, quantized, and encoded. In the most efficient compression algorithms, it is not the samples of the audio signal that are encoded, but the corresponding MDCT coefficients. (the differential between the coefficients is smaller) The accounting of the auditory perception patterns of a sound signal is carried out in the psychoacoustic analysis unit. Here, according to a special procedure, for each frequency sub-band, the maximum allowable level of quantization distortion (noise) is calculated, in which they are still masked by the useful signal of this sub-band.

The block of dynamic distribution of bits according to the requirements of the psychoacoustic model for each coding subband selects a minimum possible number of them, in which the level of distortions caused by quantization does not exceed the threshold of their audibility calculated by the model psychoacoustic.

This article will consider the functional diagrams of the audio data compression algorithms, based on µ-laws, A. The functional diagram of the compression algorithm based on the A-level compression law is shown in Fig.2. Figure 2. Functional diagram of the compression algorithm based on the A-level compression law A signal (discrete sine) is applied to the input of the compressor. After compression, the signal passes to the adder, where the noise is fed to the second input of the adder, thus simulating the additive noise of the transmission channel.

Then the noisy signal enters the input of the expander, at the output we get the reconstructed signal. The reconstructed and original signal is then fed to the adder, after which the power of the spectral noise is observed.

Simulation results (A = 87.6)
The following graphs are presented: 1-original signal, 2-signal passed through the compressor, 3-recovered signal, 4-noise power at the output of the noise generator, 5-noise power after the expander.