The Science of Audio EncodingThe Science of Audio Encoding
Audio encoding is the process of converting analog sound into digital data. This data can then be stored or transmitted in a variety of formats, such as WAV, MP3, or AAC.
There are two main types of audio encoding: lossless and lossy. Lossless encoding preserves all of the original sound data, resulting in high-quality audio but large file sizes. Lossy encoding removes some of the original sound data, resulting in smaller file sizes but lower sound quality.
The process of audio encoding can be divided into three main steps: sampling, quantization, and compression.
Sampling
The first step in audio encoding is sampling. In this step, the analog sound signal is converted into a series of discrete values. The number of times per second that the sound signal is sampled is called the sample rate. Higher sample rates result in more accurate representations of the original sound signal, but they also result in larger file sizes.
Quantization
The second step in audio encoding is quantization. In this step, each sample value is rounded to the nearest integer value. The number of bits used to represent each sample value is called the bit depth. Higher bit depths result in more accurate representations of the original sound signal, but they also result in larger file sizes.
Compression
The third and final step in audio encoding is compression. In this step, the digital audio data is compressed to reduce its file size. There are a number of different compression algorithms that can be used, each with its own advantages and disadvantages.
The most common compression algorithms for audio encoding are:
MP3: MP3 is a lossy compression algorithm that is widely used for storing and transferring audio files. MP3 files are typically much smaller than WAV files, while still providing good sound quality.
AAC: AAC is another lossy compression algorithm that offers better sound quality than MP3. AAC files are typically slightly larger than MP3 files, but they offer a noticeable improvement in sound quality.
FLAC: FLAC is a lossless compression algorithm that offers similar sound quality to WAV, but with much smaller file sizes. FLAC files are a good choice for people who want the best possible sound quality without sacrificing file size.
Final Words
Audio encoding is a complex process that involves converting analog sound into digital data. The quality of the audio that is encoded can be affected by a number of factors, including the sample rate, bit depth, and compression of the audio file.
If you are looking for the best possible sound quality, you should use a lossless audio format such as WAV or FLAC. However, if you need to store or transfer audio files over a network, you should use a lossy audio format such as MP3 or AAC.
Digital Audio Encoding is the process of converting an analog audio signal into a digital format, which can be stored, processed, and transmitted electronically. It involves the use of an Analog-to-Digital Converter (ADC) to sample and quantize the analog audio waveform into a series of binary numbers that can be interpreted by a digital device. The resulting digital audio data can then be compressed, processed, and transmitted over various digital platforms, such as the internet, CDs, DVDs, and other digital storage devices.
The Importance of Digital Audio Encoding
Digital Audio Encoding has revolutionized the way we consume and produce audio content. It has made it possible to store, edit, and transmit high-quality audio content with minimal loss of quality. Some of the benefits of digital audio encoding include:
Improved sound quality: Digital audio encoding allows for high-quality audio content that is free from the distortions and noise associated with analog audio.
Easy storage and transfer: Digital audio files can be easily stored and transferred over various digital platforms with minimal loss of quality.
Efficient compression: Digital audio files can be compressed into smaller file sizes without significant loss of quality, making it easier to store and transfer large audio files.
Greater accessibility: Digital audio content can be easily accessed over various digital platforms, including the internet, mobile devices, and other digital devices.
The Digital Audio Encoding Process
The Digital Audio Encoding process involves several steps, which include:
Sampling: The analog audio waveform is sampled at regular intervals using an Analog-to-Digital Converter (ADC).
Quantization: The sampled waveform is quantized, i.e., each sample is assigned a binary number that represents its amplitude value.
Encoding: The quantized samples are encoded into a digital format, such as WAV, MP3, or AAC.
Compression: The encoded digital audio file can be compressed using lossy or lossless compression algorithms to reduce its file size.
Lossy vs. Lossless Audio Compression
Lossy and lossless audio compression are two types of compression algorithms used in digital audio encoding. Lossy compression algorithms compress audio files by removing data that is deemed unnecessary or redundant. This results in a smaller file size but may result in a loss of audio quality. Lossless compression algorithms, on the other hand, compress audio files without any loss of quality. This results in a larger file size but maintains the original audio quality.
Bitrate and its Importance in Digital Audio Encoding
Bitrate is a measure of the amount of data used to represent each second of digital audio. It is measured in bits per second (bps) or kilobits per second (kbps). The bitrate of a digital audio file has a significant impact on its quality and file size. Higher bitrates result in higher quality audio files but also larger file sizes. Lower bitrates result in smaller file sizes but may result in a loss of audio quality.
Common Digital Audio Formats
There are several digital audio formats used in digital audio encoding, including:
WAV: WAV is a lossless audio format that is commonly used for storing high-quality audio content.
MP3: MP3 is a lossy audio format that is commonly used for compressing and storing digital audio files for playback on various digital devices.
AAC: AAC is a lossy audio format that is commonly used for compressing and streaming digital audio content over the internet.
FLAC: FLAC is a lossless audio format that is commonly used for storing high-quality audio content, similar to WAV.
Challenges in Digital Audio Encoding
Despite the many benefits of digital audio encoding, there are several challenges that must be addressed to ensure optimal audio quality. These challenges include:
Sampling rate limitations: The sampling rate of an ADC can affect the accuracy of the digital audio representation. Higher sampling rates generally result in higher accuracy, but also require larger file sizes.
Bit depth limitations: The bit depth of an ADC can affect the dynamic range and noise floor of the digital audio representation. Higher bit depths generally result in higher accuracy, but also require larger file sizes.
Compression artifacts: Lossy compression algorithms can introduce compression artifacts, such as distortion and noise, which can degrade audio quality.
Future Developments in Digital Audio Encoding
Digital Audio Encoding is an ever-evolving field, with ongoing developments aimed at improving audio quality, reducing file sizes, and enhancing accessibility. Some of the latest developments include:
High-resolution audio: High-resolution audio formats, such as MQA and DSD, offer even higher audio quality than standard digital audio formats.
Immersive audio: Immersive audio formats, such as Dolby Atmos and DTS:X, offer a more immersive listening experience by incorporating height and surround sound elements.
Object-based audio: Object-based audio formats, such as MPEG-H 3D Audio, offer greater flexibility in audio content creation and delivery by enabling individual audio objects to be separately mixed and streamed.
FAQs
1. What is digital audio encoding?
Digital audio encoding is the process of converting an analog audio signal into a digital format, which can be stored, processed, and transmitted electronically.
2. Why is digital audio encoding important?
Digital audio encoding has revolutionized the way we consume and produce audio content by providing improved sound quality, easy storage and transfer, efficient compression, and greater accessibility.
3. What are some common digital audio formats?
Some common digital audio formats include WAV, MP3, AAC, and FLAC.
4. What is the difference between lossy and lossless audio compression?
Lossy compression algorithms compress audio files by removing data that is deemed unnecessary or redundant, resulting in a smaller file size but may result in a loss of audio quality. Lossless compression algorithms compress audio files without any loss of quality, resulting in a larger file size but maintaining the original audio quality.
5. What is bitrate and why is it important in digital audio encoding?
Bitrate is a measure of the amount of data used to represent each second of digital audio. It is important in digital audio encoding because it has a significant impact on audio quality and file size.
6. What are some challenges in digital audio encoding?
Some challenges in digital audio encoding include sampling rate limitations, bit depth limitations, and compression artifacts.
7. What are some future developments in digital audio encoding?
Some future developments in digital audio encoding include high-resolution audio, immersive audio, and object-based audio.
8. What is the difference between a lossy and lossless audio format?
Lossy audio formats use compression algorithms to reduce file size, sacrificing some audio quality in the process. Lossless audio formats, on the other hand, use compression algorithms that do not compromise audio quality, resulting in larger file sizes.
9. What is a sampling rate and how does it affect audio quality?
A sampling rate is the number of times per second that an analog audio signal is measured and converted into a digital signal. The higher the sampling rate, the more accurately the digital signal represents the original analog signal, resulting in higher audio quality. However, higher sampling rates also require larger file sizes and more processing power.
10. What is bit depth and how does it affect audio quality?
Bit depth refers to the number of bits used to represent each audio sample in a digital audio file. A higher bit depth allows for a greater dynamic range and lower noise floor, resulting in higher audio quality. However, higher bit depths also require larger file sizes and more processing power.
11. What is lossless compression?
Lossless compression is a compression algorithm that reduces the size of a digital audio file without sacrificing any audio quality. This is achieved by identifying and removing redundant or unnecessary data in the audio file.
12. What is immersive audio and how does it enhance the listening experience?
Immersive audio is an audio format that uses spatial sound technology to create a more immersive listening experience. This is achieved by incorporating height and surround sound elements, which create a more three-dimensional soundstage. This allows for a more realistic and engaging listening experience, especially when combined with a surround sound system.
Conclusion
Digital audio encoding has revolutionized the way we produce and consume audio content, providing improved sound quality, easy storage and transfer, efficient compression, and greater accessibility. While there are some challenges to overcome, ongoing developments in high-resolution, immersive, and object-based audio formats promise to further enhance the digital audio experience.
References
Bosi, M., & Goldberg, R. (2012). Introduction to digital audio coding and standards. Springer Science & Business Media.
Thompson, J. (2013). Understanding digital audio. Focal Press.
Pulse Code Modulation PCM is short for Pulse Code Modulation.
Pulse code modulation is one of the encoding methods of digital communication. The main process is to sample the voice, image and other analog signals at regular intervals to discretize them, and at the same time, the sampled value is rounded and quantized according to the hierarchical unit, and the sampled value is represented by a set. of binary codes value.
Principles of speech coding
Anyone with any electronic background knows that the audio signal collected by the sensor is an analog quantity, and what we use in the actual transmission process is a digital quantity. And this involves the process of converting from analog to digital. And the digitization of analog signals must go through three processes, namely sampling, quantization and encoding, to realize the pulse code modulation (PCM, pulse code modulation) technology of voice digitization.
Convert analog signal to digital signal
Sampling
Sampling is the process of extracting sample values from an analog signal at a frequency twice or more of its signal bandwidth and changing it to a discrete sampled signal on the time axis.
Sampling rate (sample): The number of samples per second extracted from a continuous signal to form a discrete signal, expressed in Hertz (Hz).
Example: For example,
the sample rate of the audio signal is 8000 Hz.
It can be understood that the curve of the voltage change with time corresponding to the sampling in the above figure is 1 second, so the following 1 2 3 … 10 must have 1-8000 points, that is, 1 second is divided into 8000 parts, and taken out in turn The voltage value corresponding to the time of 8000 points.
quantizing
Although the sampled signal is a discrete signal on the time axis, it is still an analog signal and its sampled value is within a certain range of values and can have an infinite number of values. Obviously, it is impossible to give a group of digital code to correspond to an infinite number of samples one by one. To express the sample value by a digital code, the “rounding” method must be used to “round up” the sample value by degree, so that the sample value within a certain range of values can be changed from an infinite number of values. to a finite number of values. This process is called quantization.
Compared to the sampled signal before quantization, the quantized sampled signal is, of course, distorted and is no longer an analog signal. This quantization distortion appears as noise when the analog signal is restored at the receiving end and is called quantization noise. The size of the quantization noise depends on how you “round” the sample value.
Sampling bits: refers to the number of bits used to describe the digital signal.
8 bits (8 bits) represent 2 raised to the 8th power = 256, and 16 bits (16 bits) represent 2 raised to the 16th power = 65536; the higher the sampling number, the higher the precision.
The number of samples is indicated here to describe the minimum separation between analog signals.
Assuming our sampling number is 8 and the range of the analog signal is 2, 0, then the minimum interval between digital signals is 2/2^8 = 2/256 = 1/128;
similarly, the sample number is 16, so the minimum interval between digital signals is 2/256/256=1/(128*256)
For example
, the voltage range collected by the audio sensor is 0-3.3V, and the sampling number is 8bit (bit)
, that is, we take 3.3V/ 2^8 = 0.0128 as quantization precision.
We divide 3.3v into 0.0128 as the Y-axis step, as shown in Figure 3, 1 2 … 8 becomes 0 0.0128 0.0256 … 3.3 V. By
For example, the voltage value of a sample point is 1.652V (128 * 0.128 and 129 * 0.128) we round it to 1.65V which corresponds to a quantization level of 128.
In 1950, Bell Labs applied for a patent on Differential Pulse Code Modulation (DPCM). In 1973, P. Cummiskey, Nikil S. Jayant, and James L. Flanagan of Bell Labs introduced Adaptive DPCM (ADPCM).
Perceptual coding was first used for linear predictive coding (LPC) speech coding compression. The original concept of LPC dates back to the work of Fumitada Itakura (Nagoya University) and Saito Saito (Telegraph and Telephone in Japan) in 1966. In the 1970s, Bishnu S. Atal and Manfred R. Schroeder of Bell Labs developed a form of adaptive predictive coding (APC) called LPC, a perceptual coding algorithm that exploited the masking properties of the human ear, and later in 1980 The Code Excited Linear Prediction (CELP) algorithm appeared in the early 1990s , which achieved remarkable compression rates at the time. Perceptual coding is used by modern audio compression formats like MP3 and AAC.
Discrete Cosine Transform (DCT) by Nasir Ahmed, T. Developed by Natarajan and KR Rao in 1974, provides the basis for the Modified Discrete Cosine Transform (MDCT) used by modern audio compression formats such as MP3 and AAC. TCMD by JP Princen, A. W. Johnson, and AB Bradley in 1987, following earlier work by Princen and Bradley in 1986. MDCT is used by modern audio compression formats such as Dolby Digital, MP3, and Advanced Audio Coding (AAC).
list of lossy formats
general
Audio Coding Standard Basic Compression Algorithm abbreviation introduce Market Share (2019) Refer To
Modified Discrete Cosine Transform (MDCT) Dolby Digital (AC-3) AC3 1991 58%
ATRAC 1992 Unknown Adaptive Transformation Vocoding
MPEG layer 3 MP3 1993 49%
Advanced Audio Coding (MPEG-2/MPEG-4) CAA 1997 88%
Windows Media Audio WMA 1999 unknown
Ogg Vorbis Auger 2000 7%
Celtic Restricted Power Overlay Transformation 2011 does not apply
work work 2012 8%
digital to analog converter digital to analog converter 2015 unknown
Adaptive Differential Pulse Code Modulation (ADPCM) aptX / aptX-HD aptX 1989 unknown
DTS digital cinema system 1990 14%
Master of Quality Certification Quality Management Association 2014 unknown
Subband Coding (SBC) Audio Layer MPEG-1 II MP2 1993 unknown
musepack MPC 1997
talks
Further information: Speech coding
Linear Predictive Coding (LPC)
Adaptive Predictive Coding (APC)
Code Excited Linear Prediction (CELP)
Algebraic Code Excited Linear Prediction (ACELP)
Relaxation Code Excited Linear Prediction (RCELP)
Low latency CELP (LD-CELP)
Adaptive Multitariff (for GSM and 3GPP)
Codec2 (famous for lack of patent restrictions)
Speex (famous for lack of patent restrictions)
Modified Discrete Cosine Transform (MDCT)
AAC-LD
Constrained Energy Superposition Transformation (CELT)
Opus (mainly for real-time applications)
Encoding efficiency comparison of popular audio formats.
An audio coding format (or sometimes an audio compression format) is a content representation format used to store or transmit digital audio, such as in digital television, digital radio, and audio and video files. Examples of audio encoding formats include MP3, AAC, Vorbis, FLAC, and Opus. A specific software or hardware implementation capable of compressing and decompressing audio of a specific audio encoding format is called an audio codec; An example of an audio codec is LAME, which is one of several different codecs that implement audio encoding and decoding in MP3 audio encoding software formatting.
Certain audio encoding formats are defined by detailed technical specification documents known as Audio Encoding Specifications. Some of these specifications are written and approved as technical standards by standards bodies and are therefore called Audio Coding Standards. The term “standard” is also sometimes used for the fact that norms and formal standards.
Audio content encoded in a specific audio encoding format is usually encapsulated in a container format. So instead of raw AAC files, users often have .m4a audio files, which are MPEG-4 Part 14 containers that contain AAC-encoded audio. The container also contains metadata such as titles and other tags, and possibly an index for quick searches. One notable exception is MP3 files, which are raw audio encodings and do not have a container format. The de facto standard for adding metadata tags like title and artist to MP3s as ID3s is a hack that works by adding the tag to the MP3 and then relying on the MP3 player to recognize the snippets as malformed audio encoding, so skip the block. In a video with audio file, the encoded audio content is included with the video (in the video encoded format) within the media container format.
An audio encoding format does not specify all of the algorithms used by the codecs that implement the format. According to psychoacoustic models, an important part of how lossy audio compression works is to remove data in a way that humans cannot hear. The encoder implementer is free to choose which data to remove (depending on their psychoacoustic model).
Lossless audio encoding formats reduce the total data needed to represent the sound, but can decode it back to its original uncompressed form. Lossy audio coding formats also reduce the bit resolution of the sound in addition to compression, resulting in much less data, but at the cost of irrecoverable loss of information.
Consumer audio is often compressed using lossy audio codecs because smaller sizes are easier to distribute. The most widely used audio coding formats are MP3 and Advanced Audio Coding (AAC), both of which are lossy formats based on modified discrete cosine transform (MDCT) and perceptual coding algorithms.
Lossless audio encoding formats like FLAC and Apple Lossless are sometimes available, but at the cost of larger files.
Uncompressed audio formats such as pulse code modulation (PCM or .wav) are also sometimes used. PCM is the standard format for Compact Disc Digital Audio (CDDA), and after the introduction of MP3, lossy compression eventually became the standard.
Sound file resolution. Audio encoding and processing
Basic concepts
The sampling frequency (f) determines the number of samples stored in 1 second;
1 Hz (one hertz) is one count per second,
and 8 kHz is 8000 samples per second
The encoding depth (b) is the number of bits required to encode the level of
Memory capacity for data storage 1 channel (mono)
(to store information about a sound with a duration of t seconds, encoded with a sampling rate of f Hz and a encoding depth of b bits, 1 bit of memory is required)
For 2-channel (stereo) recording, the amount of memory required to store data for one channel is multiplied by 2
I = f b t 2
Units of measurement I – bits, b – bits, f – Hertz, t – seconds Sampling frequency 44.1 kHz, 22.05 kHz, 11.025 kHz
Audio encoding
Basic theoretical provisions
Sound time sampling. In order for a computer to process sound, a continuous audio signal must be converted to a discrete digital form using time sampling. A continuous sound wave is divided into separate small time sections, for each section a certain value of sound intensity is set.
Therefore, the continuous dependence of the loudness of the sound at time A (t) is replaced by a discrete sequence of loudness levels. On the graph, this appears to replace a smooth curve with a sequence of “steps.”
Sampling frequency. A microphone connected to the sound card is used to record analog audio and convert it to digital format. The quality of the digital sound obtained depends on the number of measurements of the sound volume level per unit time, that is, sampling rate. The more measurements are made in 1 second (the higher the sampling frequency), the more accurately the “ladder” of the digital audio signal repeats the curve of the analog signal.
Audio sample rate is the number of measurements of the volume of a sound per second, measured in Hertz (Hz). Let us denote the sampling frequency with the letter f.
The audio sample rate can vary between 8000 and 48000 sound volume measurements per second. One of three frequencies is selected for encoding: 44.1 KHz, 22.05 KHz, 11.025 KHz.
Audio encoding depth. Each “step” is assigned a specific value for the sound volume level. Loudness levels can be seen as a set of possible states N, for which encoding a certain amount of information b is required, which is called the audio encoding depth.
Audio encoding depth is the amount of information required to encode the discrete volume levels of digital audio.
If the encoding depth is known, then the number of digital audio loudness levels can be calculated using the formula N = 2b. Let the audio encoding depth be 16 bit, then the number of sound volume levels is:
N = 2 b = 2 16 = 65 536.
During the encoding process, each sound volume level is assigned its own 16-bit binary code, the lowest sound level will correspond to the code 0000000000000000 and the highest – 1111111111111111.
The quality of digitized sound. The higher the sampling frequency and depth of the sound, the better the sound of the digitized sound. The lowest quality of digitized sound, corresponding to the quality of telephone communication, is obtained at a sampling rate of 8000 times per second, a sampling rate of 8 bits, and by recording an audio track (“mono” mode). The highest quality of digitized sound, corresponding to the quality of an audio CD, is achieved with a sampling rate of 48,000 times per second, a sampling rate of 16 bits and the recording of two audio tracks (stereo mode) .
This article is intended to refer here to those who are trying to “convert” something, without understanding what they are doing and why.
To work as efficiently as possible with any object, you need to understand how it works. If the video file is for you a mysterious black box, inside which mysterious things happen, perhaps not without the help of black magic, then your effectiveness will be minimal.
So. All information on the computer is in the form of files. This, I hope, is not a surprise to anyone. Here we will start from this basic concept.
Any video file must be a container. A container is a repository of content. There are multi-structure storages – these are container formats. For example, a bento box is an example of a container. You can put sushi or tempura on it. What can you put in a video container? Well, at least image and sound, one at a time. This is a set without which there is nothing to do. What can you put to the maximum? The modern Matryoshka container allows you to put various video and audio tracks, text and graphic subtitles, fonts to display them, images and I don’t know what else.
Going back to the bento box example, note that miso cannot be poured into it; will flow in fig. Not all containers can accept all flows. There are compatibility restrictions that make life difficult.
Container examples: mpeg, avi, mkv, mp4, ogm, vob, mov, rm, divx, asf. You don’t have to look closely at the list to understand that these are standard file extensions. Of course. Because file = container.
Streams or tracks are stored inside the container. These streams have a format called a codec. And this difference must be understood with particular clarity. The container is a file format. And the codec is the stream format it contains. They are two independent things. Yes, there are some inextricably linked containers and codecs. For example, the Real Media container can only store real video and real audio streams. And vice versa, these formats cannot be stored in any other container (almost, as I have already been corrected). But they are still different concepts that should not be confused.
The codec concept usually includes the following aspects:
1) The actual data storage format.
2) Software that allows you to encode information in this format and / or decode it from it.
Examples of video codecs: divx, xvid, avc, x264, vp6, vp7, mpeg-1, mpeg-2, huffyuv.
Examples of audio codecs: mp3, ogg, ac3, aac.
While containers are generally distinguished by file extensions, codecs are distinguished by the four-character FourCC code.
The codec concept is usually associated with a kind of compression. Raw (uncompressed) streams also have their own formats, but they do not require decoding, and therefore the concept of codec is generally not applied to them.
Now let’s take a look at the most popular containers, codecs, and related issues. As a general rule, the problems we have are of two types: related to reproduction and related to editing.
MPEG is one of the oldest containers. It can store only video in mpeg-1 format and audio in mp2 format. And in a friendly way, with quite strict restrictions on the size of the image and the bitrate of the sound. Due to the age and primitiveness of the format, almost all players and publishers understand it. But for the same reasons, it became almost impossible to meet him. Nobody needs these things.
AVI is also quite old, but it is still a very useful container. It’s good because, again, all the players and all the editors get it. Almost all mpeg-based formats fit into it, as well as many that support them. The following video formats do not fit avi: avc (aka Nero AVC or Nero H.264), wmv below version 9, as well as any tinsel like actual video, which was originally designed to be incompatible with anything in the world. By sounds, supposedly anything, except Vorbis ogg.
OGM is where Vorbis ogg goes. Because the format was created on the basis of this very ogg. At the moment, he is practically ousted by the matryoshka because he can do the same, only better. It is also not compatible with any conventional software.
MKV is a nesting doll that can fit just about anything except flash video. But due to its complexity and versatility, it is still possible to do with it only things like: mount, look and dismount.
MP4 is actually modern MPEG. It only takes things that are compatible with the MPEG standard, but at the same time includes its latest updates.
MP3 (or rather, MPEG 1 Audio Level 3): no comment, compatible everywhere and by everyone, the lack of this “eternal” format is one: only two channels, which limits its use in cinema systems at home modern.
Multi-channel MP3 (5.1) MPEG 2 Audio Level 3.
WMA: Windows Media Audio, formally a better and more modern competitor to Microsoft’s mp3. It is not used much, although it is widely compatible with hardware.
OGG Vorbis is a best modern mp3 competitor from the open source community. Deprived of any license restrictions, it is used more and more frequently.
AAC: Advanced Audio Coding is Apple’s main audio format built into all of its iPads, iPhones, iTunes, etc. The main advantage is that it is technically more advanced than mp3, allowing sample rates of up to 96 kHz and theoretically a completely insane number of channels in one file, up to 48. It is also used in digital satellite radio. Just as mp3 is a compressed format, the quality of 96Kbps AAC is comparable to the quality of 128Kbps of mp3 (we are talking about two channels in both cases).
Dolby Digital (AC-3) is probably the most popular standard for digital audio in cinematography, due to the fact that it appeared on the market as early as 1995, it exists in two versions: DD2.0 (for high-quality stereo sound) and DD5 .1 – five full channels and one defective for a subwoofer. Players are compatible with all of them for obvious reasons, the bitrate is 640Kbps in all cases.
Dolby Digital Plus or E-AC-3 is an attempt to improve on the usual Dolby Digital, but the previous generation decoders and receivers do not support tracks in the Dolby Digital Plus format, the reasons for this are radical changes: the number of channels increased to 7.1, the bit rate – to 1, 7 Mbps This will not go through S / PDIF (when transmitting via such a cable, you will have to use downmix on DD5.1 or on DTS with quality loss), but HDMI normally copes with Dolby Digital Plus as of version 1.3, you can find such tracks on Blu-Ray discs …
Dolby TrueHD – We practically have 8 tracks almost uncompressed at 96 KHz / 24 bits or 6 at 192 KHz / 24 bits, the total bit rate reaches 18 Mbit / sec, which requires decoding in the player and transmission to the receiver in the analog path, or using HDMI 1.3 or higher. For Blu-Ray, this audio coding system is optional.
DTS is a lossy digital audio coding system for cinemas, which later appeared on DVD, it is analogous to Dolby Digital 5.1, but somewhat more flexible, allowing in addition to 2.0 and 5.1 to use other schemes, such as 4.0 and 4.1, there is also a choice between two fixed bit rates of 1500 Kbps and 750 Kbps. In the first case, DTS clearly outperforms Dolby Digital in sound quality; in the second, the difference between systems is controversial.
DTS-HD is a further evolution of DTS, the number of channels has been brought to 7.1 in 96KHz / 24bit mode, the bit rate can be selected between 6Mbps and 3Mbps, it is an optional audio format for Blu-Ray. The situation with the sound transmission to the receiver is almost the same as with DolbyTrueHD.
Lossless or uncompressed compressed audio encoding formats.
LPCM is simply uncompressed audio. It is usually stereo. It should not be confused with a WAV file, it is a container and there may be something other than PCM WAV inside.
APE is a specific lossless audio compression format. Loved by audiophiles.
Flac is its competitor and analog, the differences between them are beyond the scope of this review.
Lossless audio
Lossless apple
Subtitle formats.
SRT: text format, can be attached as a separate file with the same extension. Compared to the first versions of this format, the design possibilities have been significantly increased. It can also exist within MKV.
SUB / IDX is a graphic subtitle format extracted from DVD. It can fit MKV or MP4.
s2k, ssa, ass: some more advanced text formats, ass can be placed inside MKV.
smi is a textual format based on SGML, the direct ancestor of HTML.
PGS is a graphical subtitle format, the main one for Blu-Ray, but it can also exist in ts and MKV containers.
Sound information. Sound is a wave that travels through air, water, or other medium with a continuously changing intensity and frequency.
A person perceives sound waves (air vibrations) with the help of hearing in the form of sound of different volume and pitch. The higher the intensity of the sound wave, the louder the sound, the higher the frequency of the wave, the higher the pitch of the sound
The human ear perceives sound at a frequency of 20 vibrations per second (low sound) to 20,000 vibrations per second (high sound).
A person can perceive sound in a wide range of intensities, in which the maximum intensity is 10 14 times greater than the minimum (one hundred thousand billion times). To measure the volume of sound, a special unit “decibel” (dbl) is used (Table 5.1). Decreasing or increasing the sound volume by 10 dB corresponds to a decrease or increase in sound intensity by 10 times.
Table 5.1. Sound volume
Sound Volume in decibels
Lower limit of human ear sensitivity 0
Leaf whisper ten
Conversation 60
Horn 90
Jet engine 120
Pain threshold 140
Sound time sampling. In order for a computer to process sound, a continuous audio signal must be converted to a discrete digital form using time sampling. A continuous sound wave is divided into separate small time sections, for each section a certain value of sound intensity is set.
Therefore, the continuous dependence of the loudness of the sound at time A (t) is replaced by a discrete sequence of loudness levels. On the graph, this appears to replace a smooth curve with a sequence of “steps”
Sampling frequency. A microphone connected to the sound card is used to record analog sound and convert it to digital format. The quality of the digital sound obtained depends on the number of measurements of the sound volume level per unit of time, that is, the sampling frequency. The more measurements that are made in 1 second (the higher the sampling frequency), the more accurately the “ladder” of the digital audio signal repeats the curve of the dialogue signal.
Audio sample rate is the number of audio volume measurements in one second.
The audio sample rate can vary between 8000 and 48000 sound volume measurements per second.
Audio encoding depth. Each “step” is assigned a specific value for the sound volume level. Loudness levels of sound can be viewed as a set of possible states N, for which a certain amount of information I is required, which is called audio coding depth.
Audio encoding depth is the amount of information required to encode the discrete volume levels of digital audio.
If the known encoding depth, the number of digital audio volume levels can be calculated using the formula N = 2 I. Let the audio encoding depth be 16 bit, then the number of sound volume levels is:
N = 2 I = 2 16 = 65 536.
During the encoding process, each sound volume level is assigned its own 16-bit binary code, the lowest sound level will correspond to the code 0000000000000000 and the highest – 1111111111111111.
The quality of digitized sound. The higher the sampling frequency and depth of the sound, the better the sound of the digitized sound. The lowest quality of digitized sound, corresponding to the quality of telephone communication, is obtained at a sampling rate of 8000 times per second, a sampling rate of 8 bits, and by recording an audio track (“mono” mode). The highest quality of digitized sound, corresponding to the quality of an audio CD, is achieved with a sampling rate of 48,000 times per second, a sampling rate of 16 bits and the recording of two audio tracks (stereo mode) .
It should be remembered that the higher the quality of the digital sound, the greater the volume of information in the audio file. It is possible to estimate the volume of information of a digital stereo sound file with a duration of 1 second with an average sound quality (16 bits, 24,000 measurements per second). To do this, the encoding depth must be multiplied by the number of measurements in 1 second and multiplied by 2 (stereo sound):
Audio settings for video capture and transmission.
As people directly connected to the AV sphere, we constantly talk about audio coding and audio codecs, but what is it? An audio codec is essentially a device or algorithm that can encode and decode a digital audio signal.
In practice, the audio waves that are transmitted over the air are continuous analog signals. Signals are converted to digital format by a device called an analog-to-digital converter (ADC), and the reverse conversion device is a digital-to-analog converter (DAC). The codec is between these two functions and it is he who allows you to adjust some important parameters for the successful capture, recording and transmission of an audio signal: codec algorithm, sample rate, bit depth and data rate.
The three most popular audio codecs are Pulse-Code Modulation (PCM), MP3, and Advanced Audio Coding (AAC). The choice of codec determines the compression rate and the recording quality. PCM is a codec used by computers, CDs, digital phones, and sometimes SACD. The source of the PCM signal is sampled at regular intervals and each sample is the digital amplitude of the analog signal. PCM is the simplest option for digitizing an analog signal.
With the correct parameters, this digitized signal can be completely converted back to analog without any loss. Unfortunately, this codec, which provides almost complete identity with the original audio, is not very cheap, which results in large files, and these files are not suitable for streaming. We recommend using PCM to record digital images for your sources or when doing audio post-processing.
Fortunately, we always have the option of choosing a different codec that can compress digital data (rather than PCM) based on some helpful observations on the behavior of sound waves. But in this case, you have to make a compromise: all alternative algorithms are associated with “losses”, since it is impossible to completely restore the original signal, but nevertheless the result is so good that most users will not be able to notice the difference.
MP3 is an audio encoding format that uses a digital data compression algorithm that allows you to save the audio signal in smaller files. The MP3 codec is the most used by users to record and store music files. We recommend using MP3 to stream audio content as it requires less network bandwidth.
AAC is a newer audio encoding algorithm that is the successor to MP3. AAC has become the standard for MPEG-2 and MPEG-4 formats. In fact, this is also a digital data compression codec, but with less quality loss than MP3 when encoded with the same bit rate. We recommend using this codec for online streaming.
Sampling frequency (kHz, kHz)
Sample rate (or sample rate): the frequency with which the signal is digitized, stored, processed or converted from analog to digital. Time sampling means that the signal is represented by a number of its samples (samples) taken at regular intervals.
Measured in hertz (Hz, Hz) or kilohertz (kHz, kHz,) 1 kHz equals 1000 Hz. For example, 44,100 samples per second can be labeled 44,100 Hz or 44.1 kHz. The selected sample rate will determine the maximum playback frequency and, as follows from Kotelnikov’s theorem, to fully restore the original signal, the sample rate must be twice the highest frequency in the signal spectrum.
As you know, the human ear is capable of picking up frequencies between 20 Hz and 20 kHz. Given these parameters and the values shown in the table below, you can understand why 44.1 kHz was chosen as the sampling frequency for CD and is still considered a very good frequency for recording.
There are several reasons for choosing a higher sample rate, although it may seem like a waste of time and effort to reproduce sound outside the range of human hearing. At the same time, 44.1 – 48 kHz will suffice for the average listener for a high-quality solution to most problems.
Bit depth
Along with the sample rate, there is the bit depth or depth of the sound. Bit depth is the number of bits of digital information to encode each sample. Simply put, bit depth determines the “accuracy” of the input signal measurement. The larger the digit capacity, the smaller the error for each individual conversion from the magnitude of an electrical signal to a number and vice versa.
