Compression in practice. Dynamic compression Dynamic range compressed or standard
This group of methods is based on the fact that transmitted signals undergo nonlinear amplitude transformations, and in the transmitting and receiving parts the nonlinearities are reciprocal. For example, if the nonlinear function Öu is used in the transmitter, u 2 is used in the receiver. Consistent application of reciprocal functions will ensure that the overall transformation remains linear.
The idea of nonlinear data compression methods is that the transmitter can, with the same amplitude of the output signals, transmit a larger range of changes in the transmitted parameter (that is, a larger dynamic range). Dynamic range- this is the ratio of the largest permissible signal amplitude to the smallest, expressed in relative units or decibels:
| ; | (2.17) |
 .
| (2.18) |
The natural desire to increase the dynamic range by decreasing U min is limited by the sensitivity of the equipment and the increasing influence of interference and self-noise.
Most often, dynamic range compression is carried out using a pair of reciprocal functions of logarithm and potentiation. The first operation of changing the amplitude is called compression(by compression), the second - expansion(stretching). The choice of these particular functions is associated with their greatest compression capabilities.
At the same time, these methods also have disadvantages. The first of these is that the logarithm of a small number is negative and in the limit:
that is, the sensitivity is very nonlinear.
To reduce these shortcomings, both functions are modified by displacement and approximation. For example, for telephone channels the approximated function has the form (type A):
with A=87.6. The gain from compression is 24 dB.
Data compression using nonlinear procedures is implemented by analog means with large errors. Application digital media can significantly improve the accuracy or performance of the conversion. At the same time, the direct use of funds computer technology(that is, directly calculating logarithms and exponents) will not give the best results due to low performance and accumulating calculation errors.
Due to accuracy limitations, data compression by compression is used in non-critical cases, for example, for transmitting speech over telephone and radio channels.
Efficient Coding
Efficient codes were proposed by K. Shannon, Fano and Huffman. The essence of codes is that they are uneven, that is, with an unequal number of bits, and the length of the code is inversely proportional to the probability of its occurrence. Another great feature of efficient codes is that they do not require delimiters, i.e. special characters, separating adjacent code combinations. This is achieved by following a simple rule: shorter codes are not the beginning of longer ones. In this case, the continuous stream of bits is uniquely decoded because the decoder detects the shorter codewords first. Efficient codes have long been purely academic, but recently they have been successfully used in creating databases, as well as in compressing information in modern modems and software archivers.
Due to unevenness, the average code length is introduced. Average length - mathematical expectation of the code length:
moreover, l av tends to H(x) from above (that is, l av > H(x)).
The fulfillment of condition (2.23) becomes stronger as N increases.
There are two types of efficient codes: Shannon-Fano and Huffman. Let's look at how to obtain them using an example. Let's assume that the probabilities of the symbols in the sequence have the values given in Table 2.1.
Table 2.1.
Symbol probabilities
| N | |||||||||
| p i | 0.1 | 0.2 | 0.1 | 0.3 | 0.05 | 0.15 | 0.03 | 0.02 | 0.05 |
Symbols are ranked, that is, presented in a row in descending order of probabilities. After this, using the Shannon-Fano method, the following procedure is periodically repeated: the entire group of events is divided into two subgroups with the same (or approximately the same) total probabilities. The procedure continues until one element remains in the next subgroup, after which this element is eliminated, and the specified actions continue with the remaining ones. This happens until there is only one element left in the last two subgroups. Let's continue with our example, which is summarized in Table 2.2.
Table 2.2.
Shannon-Fano coding
| N | P i | ||||||
| 4 | 0.3 | I | |||||
| 0.2 | I | II | |||||
| 6 | 0.15 | I | I | ||||
| 0.1 | II | ||||||
| 1 | 0.1 | I | I | ||||
| 9 | 0.05 | II | II | ||||
| 5 | 0.05 | II | I | ||||
| 7 | 0.03 | II | II | I | |||
| 8 | 0.02 | II |
As can be seen from Table 2.2, the first symbol with probability p 4 = 0.3 participated in two procedures for dividing into groups and both times ended up in group number I. In accordance with this, it is encoded with a two-digit code II. The second element at the first stage of partition belonged to group I, at the second - to group II. Therefore, its code is 10. The codes of the remaining symbols do not need additional comments.
Typically, non-uniform codes are depicted as code trees. A code tree is a graph indicating allowed code combinations. The directions of the edges of this graph are pre-set, as shown in Fig. 2.11 (the choice of directions is arbitrary).
They navigate the graph as follows: create a route for the selected symbol; the number of bits for it is equal to the number of edges in the route, and the value of each bit is equal to the direction of the corresponding edge. The route is drawn up from the starting point (in the drawing it is marked with the letter A). For example, the route to vertex 5 consists of five edges, all but the last of which have direction 0; we get code 00001.
Let's calculate the entropy and average word length for this example.
H(x) = -(0.3 log 0.3 + 0.2 log 0.2 + 2 0.1 log 0.1+ 2 0.05 log 0.05+
0.03 log 0.03 + 0.02 log 0.02) = 2.23 bits
l avg = 0.3 2 + 0.2 2 + 0.15 3 + 0.1 3 + 0.1 4 + 0.05 5 +0.05 4+
0.03 6 + 0.02 6 = 2.9 .
As you can see, the average word length is close to entropy.
Huffman codes are constructed using a different algorithm. The coding procedure consists of two stages. At the first stage, single compressions of the alphabet are carried out sequentially. One-time compression - replacing the last two symbols (with the lowest probabilities) with one, with a total probability. Compressions are carried out until two characters remain. At the same time, a coding table is filled in, in which the resulting probabilities are entered, and the routes along which new symbols move at the next stage are depicted.
At the second stage, the actual encoding occurs, which begins from the last stage: the first of the two symbols is assigned code 1, the second - 0. After this, they move on to the previous stage. The codes from the subsequent stage are assigned to the symbols that did not participate in compression at this stage, and the code of the symbol obtained after gluing is twice assigned to the last two symbols and added to the code of the upper character 1, the lower one - 0. If the character is not further in gluing participates, its code remains unchanged. The procedure continues until the end (that is, until the first stage).
Table 2.3 shows Huffman coding. As can be seen from the table, coding was carried out in 7 stages. On the left are the symbol probabilities, on the right are the intermediate codes. The arrows show the movements of the newly formed symbols. At each stage, the last two symbols differ only in the least significant bit, which corresponds to the encoding technique. Let's calculate the average word length:
l avg = 0.3 2 + 0.2 2 + 0.15 3 ++ 2 0.1 3 + +0.05 4 + 0.05 5 + 0.03 6 + 0.02 6 = 2.7
This is even closer to entropy: the code is even more efficient. In Fig. Figure 2.12 shows the Huffman code tree.
Table 2.3.
Huffman coding
| N | p i | code | I | II | III | IV | V | VI | VII |
| 0.3 | 0.3 11 | 0.3 11 | 0.3 11 | 0.3 11 | 0.3 11 | 0.4 0 | 0.6 1 | ||
| 0.2 | 0.2 01 | 0.2 01 | 0.2 01 | 0.2 01 | 0.3 10 | 0.3 11 | 0.4 0 | ||
| 0.15 | 0.15 101 | 0.15 101 | 0.15 101 | 0.2 00 | 0.2 01 | 0.3 10 | |||
| 0.1 | 0.1 001 | 0.1 001 | 0.15 100 | 0.15 101 | 0.2 00 | ||||
| 0.1 | 0.1 000 | 0.1 000 | 0.1 001 | 0.15 100 | |||||
| 0.05 | 0.05 1000 | 0.1 1001 | 0.1 000 | ||||||
| 0.05 | 0.05 10011 | 0.05 1000 | |||||||
| 0.03 | 0.05 10010 | ||||||||
| 0.02 |
Both codes satisfy the requirement of unambiguous decoding: as can be seen from the tables, shorter combinations are not the beginning of longer codes.
As the number of symbols increases, the efficiency of the codes increases, so in some cases larger blocks are encoded (for example, if we're talking about about texts, you can encode some of the most frequently occurring syllables, words and even phrases).
The effect of introducing such codes is determined by comparing them with a uniform code:
 | (2.24) |
where n is the number of bits of the uniform code that is replaced by the effective one.
Modifications of Huffman codes
The classic Huffman algorithm is a two-pass algorithm, i.e. requires first collecting statistics on symbols and messages, and then the procedures described above. This is inconvenient in practice because it increases the time it takes to process messages and accumulate a dictionary. More often, one-pass methods are used, in which accumulation and encoding procedures are combined. Such methods are also called adaptive compression according to Huffman [46].
The essence of adaptive compression according to Huffman comes down to the construction of an initial code tree and its sequential modification after the arrival of each next symbol. As before, the trees here are binary, i.e. At most two arcs emanate from each vertex of the tree graph. It is customary to call the original vertex the parent, and the two subsequent vertices connected to it as children. Let's introduce the concept of vertex weight - this is the number of characters (words) corresponding to a given vertex, obtained when feeding the original sequence. Obviously, the sum of the children's weights is equal to the weight of the parent.
After introducing the next symbol of the input sequence, the code tree is revised: the weights of the vertices are recalculated and, if necessary, the vertices are rearranged. The rule for permuting vertices is as follows: the weights of the lower vertices are the smallest, and the vertices located on the left of the graph have the least weights.
At the same time, the vertices are numbered. The numbering starts from the lower (hanging, i.e., having no children) vertices from left to right, then moves to top level etc. before numbering the last, original vertex. In this case, the following result is achieved: the smaller the weight of a vertex, the lower its number.
The permutation is carried out mainly for hanging vertices. When permuting, the rule formulated above must be taken into account: vertices with greater weight have a higher number.
After passing the sequence (it is also called control or test), all hanging vertices are assigned code combinations. The rule for assigning codes is similar to the above: the number of bits of the code is equal to the number of vertices through which the route passes from the source to the given hanging vertex, and the value of a particular bit corresponds to the direction from the parent to the “child” (say, going to the left of the parent corresponds to the value 1, to the right - 0 ).
The resulting code combinations are stored in the memory of the compression device along with their analogues and form a dictionary. The use of the algorithm is as follows. The compressed sequence of characters is divided into fragments in accordance with the existing dictionary, after which each of the fragments is replaced with its code from the dictionary. Fragments not found in the dictionary form new hanging vertices, acquire weight and are also entered into the dictionary. In this way, an adaptive algorithm for replenishing the dictionary is formed.
To increase the efficiency of the method, it is desirable to increase the size of the dictionary; in this case the compression ratio increases. In practice, the size of the dictionary is 4 - 16 KB of memory.
 |  |
||
Let us illustrate the given algorithm with an example. In Fig. Figure 2.13 shows the original diagram (it is also called the Huffman tree). Each vertex of the tree is shown by a rectangle in which two numbers are inscribed through a fraction: the first means the number of the vertex, the second means its weight. As you can see, the correspondence between the weights of the vertices and their numbers is satisfied.
Let us now assume that the symbol corresponding to vertex 1 appears a second time in the test sequence. The weight of the vertex has changed as shown in Fig. 2.14, as a result of which the rule for numbering vertices is violated. At the next stage, we change the location of the hanging vertices, for which we swap vertices 1 and 4 and renumber all the vertices of the tree. The resulting graph is shown in Fig. 2.15. The procedure then continues in the same way.
It should be remembered that each hanging vertex in the Huffman tree corresponds to a specific symbol or group of symbols. The parent differs from the children in that the group of symbols corresponding to it is one symbol shorter than that of its children, and these children are different last character. For example, the symbols "car" correspond to the parent; then children may have the sequences "kara" and "karp".
The given algorithm is not academic and is actively used in archiver programs, including when compressing graphic data (they will be discussed below).
Lempel–Ziv algorithms
These are the most commonly used compression algorithms today. They are used in most archiving programs (for example, PKZIP. ARJ, LHA). The essence of the algorithms is that a certain set of symbols is replaced during archiving by its number in a specially generated dictionary. For example, the phrase “The outgoing number for your letter...”, which is often found in business correspondence, may occupy position 121 in the dictionary; then, instead of transmitting or storing the mentioned phrase (30 bytes), you can store the phrase number (1.5 bytes in binary decimal form or 1 byte in binary).
The algorithms are named after the authors who first proposed them in 1977. Of these, the first is LZ77. For archiving, a so-called message sliding window is created, consisting of two parts. The first part, a larger format, serves to form a dictionary and has a size of about several kilobytes. The second, smaller part (usually up to 100 bytes in size) accepts the current characters of the text being viewed. The algorithm tries to find a set of characters in the dictionary that matches those received in the viewing window. If this is successful, a code is generated consisting of three parts: the offset in the dictionary relative to its initial substring, the length of this substring, and the character following this substring. For example, the selected substring consists of the characters "app" (6 characters in total), the next character is "e". Then, if the substring has an address (place in the dictionary) 45, then the entry in the dictionary looks like “45, 6. e”. After this, the contents of the window are shifted by position, and the search continues. This is how a dictionary is formed.
The advantage of the algorithm is an easily formalized algorithm for compiling a dictionary. In addition, it is possible to unzip without the original dictionary (it is advisable to have a test sequence) - the dictionary is formed during unzipping.
The disadvantages of the algorithm appear as the size of the dictionary increases - the search time increases. In addition, if a string of characters appears in the current window that is not in the dictionary, each character is written with a three-element code, i.e. The result is not compression, but stretching.
The LZSS algorithm, proposed in 1978, has the best characteristics. It has differences in sliding window support and compressor output codes. In addition to the window, the algorithm generates a binary tree similar to a Huffman tree to speed up the search for matches: each substring leaving the current window is added to the tree as one of the children. This algorithm allows you to further increase the size of the current window (it is desirable that its size is equal to a power of two: 128, 256, etc. bytes). Sequence codes are also formed differently: an additional 1-bit prefix is introduced to distinguish uncoded characters from “offset, length” pairs.
An even greater degree of compression is obtained when using algorithms like LZW. The previously described algorithms have a fixed window size, which makes it impossible to enter phrases longer than the window size into the dictionary. In the LZW algorithms (and their predecessor LZ78), the viewing window has an unlimited size, and the dictionary accumulates phrases (and not a collection of characters, as before). The dictionary has an unlimited length, and the encoder (decoder) operates in phrase waiting mode. When a phrase that matches the dictionary is formed, a match code is issued (i.e., the code of this phrase in the dictionary) and the code of the character following it. If, as symbols accumulate, a new phrase is formed, it is also entered into the dictionary, like the shorter one. The result is a recursive procedure that provides fast encoding and decoding.
An additional compression feature is provided by compressed encoding of repeating characters. If in a sequence some characters follow in a row (for example, in the text these can be “space” characters, in a number sequence - consecutive zeros, etc.), then it makes sense to replace them with the pair “character; length” or “sign, length” ". In the first case, the code indicates the sign that the sequence will be encoded (usually 1 bit), then the code of the repeating character and the length of the sequence. In the second case (provided for the most frequently occurring repeating characters), the prefix simply indicates a repetition sign.
Dynamic compression(Dynamic range compression, DRC) - narrowing (or expanding in the case of an expander) of the dynamic range of the phonogram. Dynamic range, is the difference between the quietest and loudest sound. Sometimes the quietest sound in a soundtrack will be a little louder than the noise level, and sometimes a little quieter than the loudest. Hardware devices and programs that perform dynamic compression are called compressors, distinguishing among them four main groups: compressors themselves, limiters, expanders and gates.
Tube analog compressor DBX 566
Downward and upward compression
Downcompression(Downward compression) reduces the volume of a sound when it begins to exceed a certain threshold, leaving quieter sounds unchanged. An extreme version of downward compression is limiter. Boost compression Upward compression, on the other hand, increases the volume of a sound if it is below a threshold without affecting louder sounds. At the same time, both types of compression narrow the dynamic range of the audio signal.
Downcompression
Boost compression
Expander and Gate
If a compressor reduces dynamic range, an expander increases it. When the signal level rises above the threshold level, the expander increases it further, thereby increasing the difference between loud and soft sounds. Devices like this are often used when recording a drum kit to separate the sounds of one drum from another.
A type of expander that is used not to amplify loud sounds, but to attenuate quiet sounds that do not exceed a threshold level (for example, background noise) is called Noise gate. In such a device, as soon as the sound level becomes less than the threshold, the signal stops passing. Typically a gate is used to suppress noise during pauses. On some models, you can make sure that the sound does not stop abruptly when it reaches a threshold level, but gradually fades out. In this case, the decay rate is set by the Decay control.
Gate, like other types of compressors, can be frequency dependent(i.e. treat certain frequency bands) and can work in the mode side-chain(see below).
Compressor operating principle
The signal entering the compressor is split into two copies. One copy is sent to an amplifier, in which the degree of amplification is controlled by an external signal, and the second copy generates this signal. It enters a device called a side-chain, where the signal is measured and, based on this data, an envelope is created that describes the change in its volume.
This is how most modern compressors are designed, this is the so-called feed-forward type. In older devices (feedback type), the signal level is measured after the amplifier.
There are various analog variable-gain amplification technologies, each with its own advantages and disadvantages: tube, optical using photoresistors, and transistor. When working with digital audio (in sound editor or DAW) can use proprietary mathematical algorithms or emulate the operation of analog technologies.
Main parameters of compressors
Threshold
A compressor reduces the level of an audio signal if its amplitude exceeds a certain threshold value (threshold). It is usually specified in decibels, with a lower threshold (eg -60 dB) meaning that more audio will be processed than a higher threshold (eg -5 dB).
ratio
The amount of level reduction is determined by the ratio parameter: ratio 4:1 means that if the input level is 4 dB above the threshold, the output level will be 1 dB above the threshold.
For example:
Threshold = −10 dB
Input = −6 dB (4 dB above threshold)
Output = −9 dB (1 dB above threshold)
It is important to keep in mind that signal level suppression continues for some time after it falls below the threshold level, and this time is determined by the value of the parameter release.
Compression with a maximum ratio of ∞:1 is called limiting. This means that any signal above the threshold level is attenuated to the threshold level (except for a short period after a sudden increase in input volume). See “Limiter” below for more details.
Examples of different Ratio values
Attack and Release
A compressor provides some control over how quickly it responds to changes in signal dynamics. The Attack parameter determines the time it takes for the compressor to reduce the gain to a level determined by the Ratio parameter. Release determines the time during which the compressor, on the contrary, increases the gain, or returns to normal if the input signal level drops below the threshold value.
Attack and Release phases
These parameters indicate the time (usually in milliseconds) it will take to change the gain by a certain amount of decibels, usually 10 dB. For example, in this case, if Attack is set to 1 ms, it will take 1 ms to reduce the gain by 10 dB, and 2 ms to reduce the gain by 20 dB.
On many compressors the Attack and Release parameters can be adjusted, but on some they are pre-set and cannot be adjusted. Sometimes they are designated as “automatic” or “program dependent”, i.e. change depending on the input signal.
Knee
Another compressor parameter: hard/soft knee. It determines whether the start of compression will be abrupt (hard) or gradual (soft). Soft knee reduces the noticeability of the transition from the dry signal to the compressed signal, especially at high Ratio values and sudden increases in volume.
Hard Knee and Soft Knee compression
Peak and RMS
The compressor can respond to peak (short-term maximum) values or to the average level of the input signal. The use of peak values can lead to sharp fluctuations in the degree of compression, and even distortion. Therefore, compressors apply an average function (usually RMS) to the input signal when comparing it to a threshold value. This gives a more comfortable compression, closer to human perception of loudness.
RMS is a parameter that reflects the average volume of a soundtrack. From a mathematical point of view, RMS (Root Mean Square) is the root mean square value of the amplitude of a certain number of samples:
Stereo linking
A compressor in stereo linking mode applies the same gain to both stereo channels. This avoids stereo shifts that may result from individual processing of the left and right channels. This shift occurs if, for example, a loud element is panned off-center.
Makeup gain
Since the compressor reduces the overall signal level, it usually adds a fixed output gain option to achieve the optimal level.
Look-ahead
The look-ahead function is designed to solve problems associated with both too high and too low Attack and Release values. An attack time that is too long does not allow us to effectively intercept transients, and an attack time that is too short may not be comfortable for the listener. When using the look-ahead function, the main signal is delayed relative to the control signal, this allows you to start compression in advance, even before the signal reaches the threshold value.
The only drawback of this method is the time delay of the signal, which in some cases is undesirable.
Using Dynamic Compression
Compression is used everywhere, not only in musical soundtracks, but also wherever it is necessary to increase the overall volume without increasing peak levels, where inexpensive sound-reproducing equipment or a limited transmission channel is used (public address and communication systems, amateur radio, etc.) .
Compression is applied during playback background music(in shops, restaurants, etc.) where any noticeable changes in volume are not desired.
But the most important area of application of dynamic compression is music production and broadcasting. Compression is used to give the sound "thickness" and "drive", to better combine instruments with each other, and especially when processing vocals.
Vocals in rock and pop music are often compressed to make them stand out from the accompaniment and add clarity. A special type of compressor tuned only to certain frequencies - a de-esser - is used to suppress sibilant phonemes.
In instrumental parts, compression is also used for effects that are not directly related to volume, for example, quickly decaying drum sounds can be made longer lasting.
Electronic dance music (EDM) often uses side-chaining (see below) - for example, the bass line may be driven by a kick drum or similar to prevent bass and drums from clashing and create a dynamic pulsation.
Compression is widely used in broadcast (radio, television, internet broadcasting) to increase perceived loudness while reducing the dynamic range of the source audio (usually CD). Most countries have legal restrictions on the maximum instantaneous volume that can be broadcast. Typically these limitations are implemented by permanent hardware compressors in the air chain. Additionally, increasing perceived loudness improves the "quality" of the sound from the perspective of most listeners.
see also Loudness war.
Consistently increasing the volume of the same song remastered for CD from 1983 to 2000.
Side-chaining
Another commonly encountered compressor switch is the “side chain”. In this mode, sound compression occurs regardless of its own level, and depending on the level of the signal entering the connector, which is usually called the side chain.
There are several uses for this. For example, the vocalist has a lisp and all the “s” stand out from the overall picture. You pass his voice through a compressor, and feed the same sound into the side chain connector, but passed through an equalizer. With an equalizer, you cut out all frequencies except those used by the vocalist when pronouncing the letter “s.” Typically around 5 kHz, but can range from 3 kHz to 8 kHz. If you then put the compressor in side chain mode, the voice will be compressed at those moments when the letter “s” is pronounced. This resulted in a device known as a de-esser. This way of working is called “frequency dependent”.
Another use of this function is called "ducker". For example, at a radio station, the music goes through a compressor, and the DJ's words come through a side chain. When the DJ starts chatting, the music volume automatically decreases. This effect can also be successfully used in recording, for example, to reduce the volume of keyboard parts while singing.
Brick wall limiting
The compressor and the limiter work approximately the same way; we can say that the limiter is a compressor with a high Ratio (from 10:1) and, usually, a low Attack time.
There is a concept of Brick wall limiting - limiting with a very high Ratio (20:1 and above) and a very fast attack. Ideally, it does not allow the signal to exceed the threshold level at all. The result will be unpleasant to the ear, but this will prevent damage to sound-reproducing equipment or excess bandwidth channel. Many manufacturers integrate limiters into their devices for this very purpose.
Clipper vs. Limiter, soft and hard clipping
Compression is one of the most myth-ridden topics in sound production. They say that Beethoven even scared the neighbor's children with her:(
Okay, in fact, using compression is no more difficult than using distortion, the main thing is to understand the principle of its operation and have good control. This is what we will see together now.
What is audio compression
The first thing to understand before preparation is compression. working with the dynamic range of sound. And, in turn, is nothing more than the difference between the loudest and quietest signal levels:
So, compression is compression of the dynamic range. Yes, Just dynamic range compression, or in other words lowering the level of loud parts of the signal and increasing the volume of quiet parts. No more.
You may quite reasonably wonder why such hype is connected then? Why does everyone talk about recipes for correct compressor settings, but no one shares them? Why, despite the huge number of cool plugins, do many studios still use expensive, rare models of compressors? Why do some producers use compressors at extreme settings, while others do not use them at all? And which one of them is right in the end?
Problems solved by compression
The answers to such questions lie in the plane of understanding the role of compression in working with sound. And it allows:
- Emphasize the attack sound, making it more pronounced;
- “Setting” individual parts of instruments into the mix, adding power and “weight” to them;
- Make groups of instruments or an entire mix more cohesive, such a single monolith;
- Resolve conflicts between tools using sidechain;
- Correct the mistakes of the vocalist or musicians, leveling their dynamics;
- With a certain setting act as an artistic effect.
As you can see, this is no less significant creative process than, say, coming up with melodies or creating interesting timbres. Moreover, any of the above problems can be solved using 4 main parameters.
Basic parameters of the compressor
Despite the huge number of software and hardware models of compressors, all the “magic” of compression occurs when correct setting main parameters: Threshold, Ratio, Attack and Release. Let's look at them in more detail:
Threshold or response threshold, dB
This parameter allows you to set the value from which the compressor will work (that is, compress the audio signal). So, if we set the threshold to -12dB, the compressor will only work in those parts of the dynamic range that exceed this value. If all our sound is quieter than -12db, the compressor will simply pass it through without affecting it in any way.
Ratio or compression ratio
The ratio parameter determines how much a signal exceeding the threshold will be compressed. A little math to complete the picture: let's say we set up a compressor with a threshold of -12dB, ratio 2:1 and fed it a drum loop in which the volume of the kick drum is -4dB. What will be the result of the compressor operation in this case?
In our case, the kick level exceeds the threshold by 8dB. This difference according to the ratio will be compressed to 4dB (8dB / 2). Combined with the unprocessed part of the signal, this will lead to the fact that after processing by a compressor, the volume of the kick drum will be -8db (threshold -12dB + compressed signal 4dB).
Attack, ms
This is the time after which the compressor will respond to exceeding the response threshold. That is, if the attack time is above 0ms - the compressor begins compression exceeding the threshold signal not immediately, but after a specified time.
Release or recovery, ms
The opposite of an attack - the value of this parameter allows you to specify how long after the signal level returns below the threshold the compressor will stop compressing.
Before we move on, I strongly recommend taking a well-known sample, placing any compressor on its channel and experimenting with the above parameters for 5-10 minutes to securely fix the material
All other parameters are optional. They can differ between different compressor models, which is partly why producers use different models for specific purposes (for example, one compressor for vocals, another for a drum group, a third for the master channel). I will not dwell on these parameters in detail, but will only give general information To understand what this is all about:
- Knee or kink (Hard/Soft Knee). This parameter determines how quickly the compression ratio (ratio) will be applied: hard along a curve or smoothly. I note that in the Soft Knee mode the compressor does not operate linearly, but begins to smoothly (as far as this may be appropriate when we are talking about milliseconds) compress the sound already before the threshold value. To process groups of channels and the overall mix, soft knee is often used (as it works unnoticed), and to emphasize the attack and other features of individual instruments, hard knee is used;
- Response Mode: Peak/RMS. The Peak mode is justified when you need to strictly limit amplitude bursts, as well as on signals with a complex shape, the dynamics and readability of which need to be fully conveyed. The RMS mode is very gentle on the sound, allowing you to thicken it while maintaining attack;
- Foresight (Lookahead). This is the time during which the compressor will know what is coming to it. A kind of preliminary analysis of incoming signals;
- Makeup or Gain. A parameter that allows you to compensate for the decrease in volume as a result of compression.
First and most main advice , which eliminates all further questions about compression: if you a) understand the principle of compression, b) firmly know how this or that parameter affects the sound, and c) managed to try several in practice different models — you don't need any advice anymore.
I'm absolutely serious. If you carefully read this post, experimented with the standard compressor of your DAW and one or two plug-ins, but still did not understand in what cases you need to set large attack values, what ratio to use and in which mode to process the source signal - then you will continue to search the Internet for ready-made recipes, applying them thoughtlessly anywhere.
Compressor fine tuning recipes it's kind of like recipes for fine-tuning a reverb or chorus - it makes no sense and has nothing to do with creativity. Therefore, I persistently repeat the only correct recipe: arm yourself with this article, good monitor headphones, a plug-in for visual control of the waveform, and spend the evening in the company of a couple of compressors.
Take action!
Records, especially older ones that were recorded and produced before 1982, were much less likely to be mixed to make the recording louder. They reproduce natural music with a natural dynamic range that is preserved on the record and lost in most standard digital or high-definition formats.
There are exceptions to this, of course—listen to Steven Wilson's recent album from MA Recordings or Reference Recordings and you'll hear just how good digital audio can be. But this is rare; most modern sound recordings are loud and compressed.
Music compression has come under a lot of criticism lately, but I'm willing to bet that almost all of your favorite recordings are compressed. Some of them are less, some are more, but still compressed. Dynamic range compression is a scapegoat for bad-sounding music, but highly compressed music is nothing new: listen to Motown albums from the '60s. The same can be said about the classic works of Led Zeppelin or the younger albums of Wilco and Radiohead. Dynamic range compression reduces the natural relationship between the loudest and softest sounds in a recording, so a whisper can be as loud as a scream. It's quite difficult to find pop music from the last 50 years that hasn't been compressed.
I recently had a nice chat with Tape Op magazine founder and editor Larry Crane about the good, the bad, and the ugly aspects of compression. Larry Crane has worked with bands and artists such as Stefan Marcus, Cat Power, Sleater-Kinney, Jenny Lewis, M. Ward, The Go-Betweens, Jason Little, Eliot Smith, Quasi and Richmond Fontaine. He also runs the recording studio Jackpot! in Portland, Oregon, which was home to The Breeders, The Decemberists, Eddie Vedder, Pavement, R.E.M., She & Him and many, many others.
As an example of surprisingly unnatural-sounding but still great songs, I cite Spoon's 2014 album They Want My Soul. Crane laughs and says he listens to it in the car because it sounds great there. Which brings us to another answer to the question of why music is compressed: because compression and additional “clarity” make it easier to hear in noisy places.
Larry Crane at work. Photo by Jason Quigley
When people say they like the sound of an audio recording, I think they like the music, as if sound and music were inseparable terms. But for myself, I differentiate these concepts. From an audiophile's perspective, the sound may be rough and raw, but that won't matter to most listeners.
Many are quick to accuse mastering engineers of overusing compression, but compression is applied directly during recording, during mixing, and only then during mastering. Unless you were personally present at each of these stages, you will not be able to say what the instruments and vocal parts sounded like at the very beginning of the process.
Crane was on a roll: “If a musician wants to intentionally sound crazy and distorted like the Guided by Voices records, then there’s nothing wrong with that—the desire always outweighs the sound quality.” The performer's voice is almost always compressed, and the same thing happens with bass, drums, guitars and synthesizers. Compression maintains the volume of vocals at the right level throughout the song or stands out a little from the rest of the sounds.
Properly done compression can make drums sound more lively or intentionally strange. To make music sound great, you need to be able to use the necessary tools. This is why it takes years to figure out how to use compression without overdoing it. If the mix engineer compresses the guitar part too much, the mastering engineer will no longer be able to fully restore the missing frequencies.
If musicians wanted you to listen to music that had not gone through the stages of mixing and mastering, they would release it onto store shelves straight from the studio. Crane says the people who create, edit, mix and master recorded music aren't there to get in the way of musicians - they've been helping artists since the beginning, for more than a hundred years.
These people are part of the creation process that results in amazing works of art. Crane adds, "You don't want a version of 'Dark Side of the Moon' that hasn't been mixed and mastered." Pink Floyd released the song the way they wanted to hear it.
