why is audio compression important Archives - Page 3 of 3

Compression and compression methods of audio signals

Free Download Mp4Gain

Compression and compression methods of audio signals (types, differences, use)

Audio Compression

Basics of the analog-to-digital conversion principle, sound conversion and compression method, existing sound storage formats. Programs to convert and process sound and audio files. Application of these programs in linguistic research.

Bit rate is the amount of information per unit of time. In general, the bit rate is the number of bits that we spend encoding a sound with a duration of 1 second.

Analog-to-digital converter (ADC): A device that converts an input analog signal into a binary code (digital signal). The reverse conversion is done using a DAC (digital-to-analog converter, DAC). Typically, an ADC is an electronic device that converts voltage into a binary digital code. However, some non-electronic devices with digital output must also be classified as ADCs, such as some types of angle-to-code converters. The simplest one-bit binary ADC is a comparator.

The circuit to convert an audio signal from analog to digital:

Sampling is the transformation of continuous images and sound into a set of discrete values in the form of codes.

Quantization is the process of aligning a set of musical notes to a grid.

Compression (compression) of audio data is a process of lowering the bit rate by reducing the statistical and psychoacoustic redundancy of a digital audio signal.

The underlying idea behind all lossy audio compression techniques is to neglect the subtle details of the original sound that are beyond the reach of the human ear.

Codec (CoDec) is an abbreviation for compressor and decompressor. Basically, a codec is a collection of files, drivers, and libraries required to package a video or audio file into a compressed format and play the compressed file.

Formats:

AAC (Advanced Audio Coding) is an audio file format with less quality loss when encoding than MP3 of the same size. The format also allows you to compress without losing the quality of the source (ALAC AAC profile).

AAC (Advanced Audio Coding) was originally created as a successor to MP3 with improved encoding quality. The AAC format, officially known as ISO / IEC 13818-7, was released in 1997 as the new seventh part of the MPEG-2 family. There is also the AAC format known as MPEG-4

Apple AIFF: This file type is standard for Apple Macintosh systems and sound processing systems built on top of it. Apple AIFF stands for Audio Interchange File Format, an audio interchange file format, it is somewhat similar to WAV. Its peculiarity is that it allows you to place additional information along with the sound wave, in particular WaveTable samples (examples of the instrument sound together with synthesizer parameters), which improves the quality of the final result. Although today Apple computers are capable of playing files of almost any format, including MP3.

FLAC (Free Lossless Audio Codec) is a popular free codec for audio compression. Unlike lossy Ogg Vorbis, MP3 and AAC codecs, it does not remove any information from the audio stream and is suitable for both daily listening and archiving of audio collection. Today, the FLAC format is compatible with many audio applications.

Free Download Mp4Gain

Mp4Gain Main Window

Mp4Gain Features

Free Download Mp4Gain

Digital audio compression methods

Digital audio compression methods

audio compression

Lossless compression

AUDIO COMPRESSION

Generally speaking, the meaning of lossless compression is as follows: some pattern is found in the original data, and taking this pattern into account, a second stream is generated, uniquely describing the original. For example, to encode binary sequences in which there are many zeros and few ones, we can use the following replacement:

00> 0
01> 10
10> 110
11> 111

In this case, sixteen bits:
00 01 00 00 11 10 00 00

will be converted to thirteen bits:
0 10 0 0 111 110 0 0

If we write a compressed string without spaces, we can still add spaces in it, which means restoring the original sequence.

FLAC (Free Lossless Audio Codec)
Coding principle: the algorithm tries to describe the signal with this function so that the result obtained after subtracting it from the original (called difference, remainder, error) can be encoded with the minimum number of bits.

When the model is fitted, the algorithm subtracts the approximation from the original to obtain a residual signal (error), which is then losslessly encoded.

Lossy compression (MP3, AAC, WMA, OGG)
Using a lossy compression algorithm, the size of an MP3 file with an average bit rate of 128 kbps is approximately 1/11 of the original file of an Audio CD (uncompressed audio in CD-Audio format has a rate bit rate of 1411.2 kbps). MP3 files can be created at high or low bit rates, which affects the quality of the result.

The principle of compression is to reduce the precision of some parts of the sound flow, which is almost indistinguishable for most people. The audio signal is divided into segments of equal length, each of which, after processing, is packed into its own frame (frame). Spectral decomposition requires continuity of the input signal; therefore the table above and below are also used for calculations. The audio signal contains harmonics with a lower amplitude and harmonics that are close to the strongest; Such harmonics are cut off, as the average human ear will not always be able to determine the presence or absence of such harmonics. This characteristic of hearing is called the masking effect. It is also possible to replace two or more nearby peaks with an averaged one (which, as a rule, leads to sound distortion). The cutoff criterion is determined by the outflow requirement. Since the entire spectrum is relevant, the high-frequency harmonics are not cut off, but are only selectively removed to reduce information flow due to spectrum sparsity. After spectral removal, mathematical compression and frame packing methods are applied.

Masking effect
In certain cases, a sound can be hidden by another sound. For example, talking near the railroad tracks can be completely impossible if a train passes. This type of effect is called masking. A weak sound is said to be masked if it becomes indistinguishable in the presence of a louder sound.

Simultaneous masking
Any two sounds when heard simultaneously have an impact on the perception of the relative volume between them. A louder sound reduces the perception of a weaker one, until the disappearance of your hearing. The closer the frequency of the masked sound is to the frequency of the masker, the more it will be hidden. The masking effect is not the same when the masked sound is shifted down or up in frequency with respect to masking. Low-frequency sound masks high-frequency sound. However, it is important to note that high-frequency sounds cannot mask low-frequency sounds.

Time masking
This phenomenon is similar to frequency masking, but time masking occurs here. When the masking sound is stopped, the masking remains inaudible for some time. Under normal conditions, the temporary masking effect lasts significantly less. The masking time depends on the frequency and amplitude of the signal and can be up to 100 ms.
In the case where the masking tone appears at a time after masking, the effect is called post-masking. When the masking tone appears before the masking (this is also possible), the effect is called premasking.

Post-stimulus fatigue
Often after exposure to loud, high-intensity sounds, a person’s hearing sensitivity drops dramatically. Recovery to normal thresholds can take up to 16 hours. This process is called “temporary change in hearing sensitivity threshold” or “post-stimulus fatigue.”

Improved efficiency of digital audio data compression algorithms.

Improved efficiency of digital audio data compression algorithms.

audio compression

The relevance of the work. Methods for encoding high quality (HS) audio signals have become very widespread in the last decade in the field of broadcasting, digital sound recording, and home audio and video equipment. There’s even a fast-growing new class of consumer electronics: portable MP3 players.

Audio Compression:

Digital television and radio transmission networks are being developed, providing consumers with high-quality images and sound with a wide coverage area. The popularity of radio and television broadcasts over the Internet and mobile phone networks is increasing. All these technological innovations have become economically viable, and in some cases even technically possible, thanks to the use of highly efficient digital video and audio data compression algorithms, such as MPEG-1 ISO / IEC 11172, MPEG-2 TSO / IEC 13818, MPEG-4 ISO / IEC FCD 14496, ATSC Dolby AC-3. At the same time, due to the economic advantages of using these algorithms, which make it possible to reduce the bandwidth requirements of the transmission channels or the capacity of the information carriers by an order of magnitude, it is necessary to compensate with a certain decrease in the sound quality. During the era of the dominance of digital audio CDs, consumers have created a requirement for high sound quality from any sound reproduction equipment. The efforts of algorithm developers for encoding audio signals have always been aimed at ensuring that the quality of decoded audio material is no worse than that of a CD. Sound quality is often the determining factor in the economic success of digital broadcasting services or digital sound distribution services like iTunes). Further,

It is obvious that the problem of improving the quality of audio coding is today one of the key problems for the sound recording industry, the audio broadcasting industry and the manufacturers of various multimedia systems.

The basic principle of operation of highly efficient audio coding systems is to use the properties of the human auditory system, mainly the phenomenon of masking. The phenomenon of psychoacoustic masking is due to the biophysical and neuronal processing of sound signals by the human auditory system [173]. At the same time, part of the sound information does not affect the acoustic perception of the sound signal due to the presence of components with greater intensity in it. Therefore, the strongest components of the audio signal form the so-called masking thresholds. Sound information with a signal energy level below the masking threshold is not perceived by the auditory system. In the traditional digital representation of audio signals using pulse code modulation (PCM), time-sampled samples of the original signal are represented using a specific number of bits in the code word. The finite precision of the instantaneous values of a continuous analog signal introduces an error in the signal, the so-called quantization noise. The idea of encoding audio signals with the elimination of psychoacoustic redundancy is to combine psychoacoustic analysis and the quantization mechanism of audio signals [112]. In this case, the digitally encoded signal is converted into a time-frequency representation, as close as possible to the time-frequency resolution of the human auditory system. Psychoacoustic analysis determines the masking thresholds at each point in the time-frequency representation of the encoded signal, and the quantizer re-quantizes the signal with the minimum possible number of bits per sample, in which the increasing quantization noise is still below the masking thresholds. Thus, a compact representation of audio signals can be achieved without subjective degradation of sound quality. It is obvious that the efficiency and quality of such systems depend mainly on the precision of the psychoacoustic analysis. a compact representation of audio signals can be achieved without subjective degradation of sound quality. It is obvious that the efficiency and quality of such systems depend mainly on the precision of the psychoacoustic analysis. a compact representation of audio signals can be achieved without subjective degradation of sound quality. It is obvious that the efficiency and quality of such systems depend mainly on the precision of the psychoacoustic analysis.

Does MP3 affect the sound quality?

The compression of songs affects the quality, but the losses are not necessarily audible.

Is compression of MP3 songs harmful to the sound quality? Whether it is HD music or “normal” definition, the question of compression remains. The advantage is that the weight of the songs is reduced, so they take up less space in the memory of a phone or a portable music player. With standard MP3 compression, a music album ranges from 500 MB to 45 MB.

But by the way, the music is damaged. The sound seems a little less natural, less precise, less dynamic. Some of the audio information is literally destroyed. It doesn’t always sound good, but for some songs the difference is clear until everyone will notice.

Fortunately, you can improve the quality of an MP3 song by compressing it with less force. The loss of sound quality becomes less clear, but in return the song weighs more. MP3 isn’t the only compressed music format that corrupts music. The most famous competitors are AAC, Ogg Vorbis and WMA. MP3 is not the most efficient compression format, this title applies to the Ogg Vorbis, but it is still a good option. All music players can play MP3 and online record stores prefer this format.

Lossless compression

However, some music lovers are reluctant to MP3. They swear by “nondestructive” compression, which does not remove sound information. The music has been completely preserved: we hear absolutely no difference. The best known non-destructive formats are Flac, APE and Alac. Unfortunately, not all electronic devices can play music recorded in these formats. Few artists offer their music in “non-destructive” compression. And the weight of the parts thus compressed is still very heavy. An album quickly reaches several hundred megabytes. However, the Flac stands out as the reference format for the most demanding music lovers.

Is it reasonable to keep using MP3? This remains a smart choice for most music lovers, as long as they choose an appropriate compression ratio. Which one to choose: 192 kbit / s, 256 kbit / s or 320 kbit / s? The stronger the compression, the lighter the number, but the lower the quality. With 128 kbit / s, the sound has clearly deteriorated, most of us can hear it. At 192 kbit / s, degradation becomes difficult for most of us to observe except for some rare numbers.

With 256 kbit / s, you have to have a musical ear and good sound equipment to make the difference. With 320 kbit / s, you need a well-trained ear and highly accurate audio equipment to make a difference. We only see a difference in quality in certain titles and only in certain passages. Therefore, most of us can settle for 192 kbit / s recording. Music lovers should expect a minimum of 256 kbit / s. And professionals will choose formats of 320 kbit / s or ‘lossless’.

Data compression techniques

It is evident that coding techniques for multimedia information contain large amounts of data that require memory space for recording and high transmission speed for transfer to other digital systems.

These needs can be met by reducing the space occupied by the data with special compression techniques. Compressed data cannot be used directly for processing, viewing, or playback. Compression techniques are used by special programs immediately before data storage or transmission. During the read or receive phase, similar programs perform decompression. Compression can be done on the basis that information encoding techniques dedicate an always equal amount of memory to each information element (be it a character, a pixel or a sound sample), regardless of their statistical frequency and its significance.

The compression techniques developed so far are more than a hundred but grouped into two categories:

Compression without loss of information.

Lossless compression techniques are based on compact coding of the same data streams or coding with a small number of bits of the most statistically frequent data.

This compression is completely reversible and the decompression program returns the exact bit sequence as it originally was. For this reason, loss-free technique is applicable to any type of data, including executable texts and programs, although the achievable compression factor is not very high: values usually range from 2: 1 to 4: 1. Of course, these results vary depending on the type of input data.

RLE encoding

The RLE (Run Length Encoding) compression technique is oriented to equal byte sequences. In the original version, it provides the introduction of a special character that indicates the beginning of a sequence, and instead of encoding the same characters in the sequence one by one, it encodes only the first one, followed by a number indicating where many times drawn and repeated. Specifies with the Sc character at the beginning of the sequence, the statement

these ******** are eight stars… these Sc * 8 are eight stars

where 8 is not encoded as an ASCII character but as a binary number.

The decompression program interprets the next byte as a counter and rebuilds the original sequence.

For image compression, RLE encoding only works well with images that contain large areas of uniform color, but are not very effective with complex images.

Compression with loss of information.

Loss-free compression techniques are not sufficient to solve the problem of the huge amount of data generated by encoding multimedia information, e.g. Video images while allowing better use of memory space on disks or data transmission lines. High resolution. , audio or video.

However, to try to solve this problem, it is necessary to remember that multimedia information, although subject to transformation, can remain understandable; This allows for compression factors that are higher in some orders of magnitude than those observed.

These interventions can be studied based on the behavior (vision and hearing) of our sensory systems to reduce the required memory without obvious changes in information content. Compression techniques that do this are called “lossy” since the least significant piece of information is irreversibly suppressed. Therefore, it appears that the bitstream after decompression is different from the original, and therefore these techniques cannot be used for other types of information, e.g. Text. Furthermore, the information thus compressed is not suitable for further processing as the loss introduced with each subsequent step becomes more and more apparent.

What is video encoding and how does it work?

The technique of compressing videos

What do we mean when we talk about video coding or, as industry experts generally call it, video coding?

Simply put, video encoding is the process of compressing and converting video content. The ultimate goal is to use less storage space, use less bandwidth, and make the user experience smoother. It goes without saying that the compression process causes a significant loss of information. The more data that is applied, the more data is deleted in the video. The result is a different version of the original due to missing data.

Why is video coding so important?

Video encoding is essential for transmission because it simplifies the transmission of video on the Internet through a compression process. Compression reduces the bandwidth required while providing a high quality experience. Without this, raw video content would not allow many users to view content on the Internet due to insufficient connection speeds. The protagonist of this process is the bit rate or the speed of digital data transmission that can be transmitted in a certain time interval in a communication channel. When streaming, the bit rate determines whether users can easily view the content or are exposed to video buffering.

Another fundamental aspect of video coding is compatibility. Indeed, sometimes the content is already compressed to an appropriate size, but it still needs to be encoded to be compatible with different devices and applications, although this is often referred to as transcoding.

The video encoding process is governed by video codecs, which are compression standards that are created through software or hardware applications. Each codec consists of an encoder for compressing the video and a decoder for restoring an approximation of the video for playback. The name codec is actually derived from the merging of the words “encoder” and “decoder”.

But what is the best codec?

It depends on the type of video. On this occasion we will describe the most commonly used.

To stream high quality video over the Internet, H.264 is arguably the most widely used codec for most multimedia traffic. This codec is considered to be of excellent quality, coding speed and compression efficiency, although it is not as efficient as the later HEVC (High Efficiency Video Coding) compression standard, also known as H.265. H.264 also supports 4K video streaming, a real advance for a codec created in 2003.

Now that we have an overview of codecs, let’s look at some compression techniques.

Compression techniques

The most common compression technique is scaling the resolution. The higher the resolution of a video, the more information is contained in each picture. One way to reduce the amount of data is to reduce the size of the image and then scan it again. As a result, fewer pixels are generated, which reduces the level of detail of the image, which has a positive effect on the amount of information required. This process allows you to set multiple quality levels for a video that correspond to different resolutions created. A practical example is if you are watching a movie in streaming before playing it, you can actually choose the resolution at which you want to watch it, provided your device
Support him

One video compression technique that may not be widely used is the interframe. This process reduces “redundant” information from one frame to another.

Another technique is the P-frame, short for predictive frame, which means that it can look back at an i-frame or another P-frame and understand whether the same images are present. In this case, this part is excluded for reasons of space.

B-Frame, on the other hand, is the bidirectional predictive frame that offers good compression without affecting the viewing experience. However, this technique requires a higher coding profile.

Another technique is that which makes it possible to intervene in the color. This process, called “chroma subsampling”, tries to maintain the brightness of the image, which affects the quality of the color. Finally, another method of compressing videos is to reduce the number of frames per second.

Audio compression, an explanation

Audio compression can be somewhat confusing at first due to the fact that the tools to implement it often have many elements that interact with each other and can be a headache.

Added to all this is the fact that audio / sound compression is often confused with compression in terms of digital formats (MP3 for example), which is a much more complex principle.

That is why we made this guide that aims to attack the most common doubts regarding compressors. The ones I had and the ones you probably have at the moment.

Let’s move on to the important:

What are compressors?

They are essentially an automatic volume or level control.

Let me explain: They are the equivalent of the fader of a console operated by a person in real time, that person has the function of lowering the fader when the volume of an element suddenly rises excessively. All this to control the dynamic range of said element and prevent it from going out of plane.

So what the compressor does in essence is reduce the level of a signal with parameters that are set by the user and that modify how it behaves.

How do they work?

Threshold and knee audio compression
An example of an acting audio compressor showing a 4: 1 reduction contrasting it with the signal without any reduction (1: 1)

Comparing signals, that is to say: a signal enters the compressor, for example the voice we were talking about before and we set a certain level (threshold or treshold) which, if exceeded, causes the compressor to act reducing the level of said voice at the output as if it were the fader on a console.

So the compressor is all the time comparing the input signal against this threshold and reducing the signal at the output if it passes it. On the other hand, the amount of reduction at the output is not always the same, but can be modified by the user with another parameter.

What are all those knobs?

Compressors have various user-modifiable parameters that appear in the form of knobs on both digital and hardware models. Let’s see what they are:

Threshold or Treshold: we tell the compressor that if the signal goes above a certain level, it reduces it in gain. The lower the amount of signal enters the compression and therefore there will be greater reduction in gain. A detail to keep in mind is that in digital models the threshold will appear as a negative number, in essence the more negative that number is, the lower the threshold and the more signal is compressed.
Compression ratio or Ratio: here we tell the compressor to reduce the signal that exceeds the threshold by a certain proportion established by us. For example, if our signal passes the threshold by 10 decibels and we want it to decrease by 5 decibels, we put a ratio of 2: 1 (it works as a division). At higher rates, there will be a greater reduction, but also the compression may start to be noticeable, which that we generally don’t want to happen. What is sought is that it be transparent so that the listener does not realize that the signal was manipulated.

Attack or Attack: it is the time in seconds (generally in the order of milli seconds) that the compressor takes from the moment the signal passes the threshold to the complete reduction in gain that we set with the compression ratio. Keep in mind that the compressor essentially acts immediately, but it is this time that determines how it interacts with the envelope of the signal to be compressed.

Release: is the time in milli seconds that the compressor takes to return to unity gain once the signal stops being above the set threshold. In the same way that with the attack the release can modify the envelope of the sound in question and therefore is very important in the operation of the compressor.

Knee: it is a parameter found in some compressors that modifies the way in which the compressor begins to act, the name is due to the fact that the curve that describes the way in which the compressor begins to act is similar to a knee (knee in English ).
So that we understand better when we talk about soft knee we are talking about that the compressor starts to act gradually before the set threshold and reaches its compression ratio established in this way. Instead, a hard knee compressor will only act when the signal goes beyond the established threshold and therefore more aggressively.

Make up gain or output gain: is the parameter that controls the compressor’s output gain, after having activated and reduced the signal by a number of decibels. What is sought in general is that what was reduced in level is re-gained and therefore make the parts that had less volume now approach those that were compressed.