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Mp3: Audio Bit Depth, Sample Rate and Bit Rate

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Mp3: Audio Bit Depth, Sample Rate and Bit Rate

(a) Regarding bit depth. Bit depth is also called sampling bit depth, and the bit depth of the audio determines the dynamic range.

Our common 16-bit (16-bit) can record a dynamic range of about 96 decibels. Well, roughly you can know that each bit can record about 6 decibels of sound. Similarly, the 20-bit recordable dynamic range is about 120 dB; 24 bits is about 144 dB.

If we define 0dB as the maximum value, then the sound amplitude is calculated by extension down, then the dynamic range of CD audio is “-96dB ~ 0dB”, and so on, the dynamic range of 24Bit HD-Audio high – the audio definition is “-144dB~0dB”. It can be seen that at higher bit depths, a greater dynamic range is available and lower levels of detail can be recorded.

(2) Regarding the sampling frequency.

What is the most intuitive effect of sample rate? Affects the expressiveness of the sound’s frequency range. The higher the sample rate, the larger the frequency range that can be expressed. 44.1KHz sampling rate can express the frequency range from 0Hz to 22050Hz; 48KHz sampling rate can express the frequency range from 0Hz to 24000Hz; 96KHz sampling frequency can express the frequency range from 0Hz to 48000Hz. The average frequency range that the human ear can hear is about 20Hz-20000Hz.

Combining the two above, if you see a parameter:

16Bit 44.1KHz, means this digital audio can express “96dB dynamic range” and “0Hz-22050Hz” frequency range;

24Bit 48KHz, which means this digital audio can express “144dB dynamic range” and “0Hz-24000Hz” frequency range.

(3) Audio bit rate, also called bitrate or bit rate.

Bit rate refers to the amount of information that can pass through a data stream per second, and can also be understood as: how many bits of data per second are used to represent.

In principle, the higher the audio bitrate, the better the quality.

However, in the case of lossy compressed audio, different compression algorithms, even at the same bitrate, can lead to completely different sound quality results.

Typical Representative: WMA 96kbps audio format sound quality is obviously better than MP3 96kbps sound quality. Why is this so? Differences in data usage due to different compression algorithms. For another example, if MP3 is compressed below 48kbps, it’s already terrible, and if it’s AAC audio format, the sound quality is obviously better than MP3 at the same 48kbps bitrate.

For lossless compressed audio, even though the bitrate is completely different, the final sound quality is the same. For example, if the same WAV file is compressed in FLAC format and APE format, the bit rate of the output file is not the same, but the sound quality is the same. Even in the same format, the compression level is different and the bitrate is completely different, but the end result, the sound quality remains the same (but when encoding and decoding, the CPU usage is different and the encoding time is also different).

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Mp3, what is bit depth and how does it affect the quality of an mp3?

Bitrate is not the same as bit depth

We have explained in previous articles that sound is a wave that propagates through the air. And the act of digitizing it is based, on the one hand, on the number of samples that are taken, in order to be able to draw it with enough gfidelity, but that, if we have an X,Y graph, represents only one of the axes.
The other axis is represented by the depth, that is, we already have how many samples are taken per second, but we need to have on the other side, how many possibilities we have to “capture” the data that each sample captures.

If we have a bit depth of 16 then we will have a little more than 250 different values to draw the wave.

If instead we use a bit depth of 24 bits, we will have millions of different values. Which allows us in treoria to have much greater detail or fidelity.

All this is what the theory tells us. It’s like with colors, with a bit depth of 16 bits we will have 250+ options to describe, let’s say a green color, instead with 24b we will have millions of possible variants.

Obviously the first thing we will have to ask ourselves is if the device is capable of reproducing millions of different colors or variants in sound.

We must also ask ourselves if the human ear will be able to pick up these differences.

Even, and we won’t dwell on it, “noise” plays an important role here.

We would say that in general terms for the sound a bit depth equal to or greater than 16 is already enough to have an important quality.

Audio bit depth

Audio bit depth

16 bit vs. 24 bit Audio, What Should You Record At? (FAQ Series) - YouTube

In digital audio using pulse code modulation (PCM), bit depth is the number of bits of information in each sample and corresponds directly to the resolution of each sample. Examples of bit depths include digital audio CD, which uses 16 bits per sample, and DVD-Audio and Blu-ray Disc, which can support up to 24 bits per sample.

Live Digital Audio in Plain English Part 1 - SoundGirls.org

In basic implementations, changes in bit depth mainly affect the noise floor due to quantization error, that is, signal-to-noise ratio (SNR) and dynamic range. However, techniques such as dithering, noise shaping, and oversampling mitigate these effects without changing the color depth. Bit depth also affects baud rate and file size. Bit depth is only relevant with respect to digital PCM signal. Non-PCM formats, such as lossy compression formats, have no associated bit depth.

Binary representation A PCM signal is a sequence of digital audio samples containing data that provides the information necessary to reconstruct the original analog signal. Each sample represents the amplitude of the signal at a specific point in time, and the samples are evenly distributed over time.

Amplitude: This is the only information that is explicitly stored in the sample and is usually stored as an integer or a number with a floating point number, encoded as a binary number with a fixed number of digits: the depth of sample bits, also called word length. or word size. Resolution indicates the number of discrete values that can be represented in a range of analog values. The resolution of binary integers increases exponentially with increasing word length. Adding one bit doubles the resolution, adding twice doubles the resolution, and so on. The number of possible values that can be represented by an integer bit depth can be calculated using 2 n, where n is the bit depth. Thus, a 16-bit system has a resolution of 65,536 (2 16) possible values.

PCM integer audio data is usually stored as signed numbers in binary complement format. Many audio file formats and Digital Audio Workstations (DAWs) now support PCM formats with floating point samples. Both the WAV file format and the AIFF file format support floating point representations. Unlike integers, whose bit structure is a single series of bits, a floating point number consists of separate fields, which are mathematically linked to form a number. The most common standard is IEEE 754, which consists of three fields: the sign bit, which indicates whether the number is positive or negative, the exponent, and the mantissa, which is increased by the exponent. Mantissa is expressed as a binary fraction in IEEE base two floating point format.

Floating point The resolution of floating point samples is less easy than that of integer samples because the floating point values are not uniformly distributed. In floating point representation, the space between two adjacent values is proportional to the value. This significantly increases the SNR in an integer system because the precision of a high-level signal will be the same as the precision of an identical signal at a lower level.

The tradeoff between floating point and integer values is that the distance between large floating point values is greater than the space between large integer values of the same bit depth. Rounding a large floating point number results in more error than rounding a small floating point number, while rounding a whole number always results in the same level of error.

In other words, the integers have a uniform rounding, always rounding the least significant bit to 0 or 1, and the floating point has a uniform signal-to-noise ratio, the quantization noise level is always proportional to the signal level. The floating point noise floor will increase as the signal increases and will decrease as the signal decreases, resulting in audible drift if the bit depth is small enough.

What is the audio bit depth?

Understand what bit depth is, how it works, and how this feature will affect the quality of music during auditions;

Currently, many of those who are looking for quality audio or quality music keep mentioning “Hi-Res”, FLAC 24-bit, and MQA (Master Quality Audio) files. This is a growing trend in high-end smartphones that are trying to offer higher audio quality both in their DAC and in support of advanced Bluetooth audio codecs like LDAC, developed by Sony. Additionally, there are music streaming services that promise lossless audio quality, like Tidal.

BitDepth

The promise made by audio equipment manufacturers, developers of audio streaming and music streaming formats, is simple: superior audio quality due to the increased amount of data, also known as bit depth or English bit depth . There are 24 bits of 1 and 0 versus 16 bits on the CD. Of course, these high-resolution files are more expensive due to their quality, but the more bits, the better the result will be when listening to music, right?

Bitdepth

Low resolution audio is usually displayed using a jagged wave graph (with ladders). Source: soundguys
Low resolution audio is usually displayed using a jagged wave graph (with ladders). Source: soundguys
Well, the answer to the previous question is: not necessarily. The argument for a value in increasing bit depth is not based on something scientific, but on the distortion of what is actually happening and the exploitation of consumer ignorance about the media they are consuming. That is, it is a fact that stores selling 24-bit tracks reap far more benefits than a real improvement in promised sound quality.

Bit depth and sound quality.

The greatest example of companies selling 24-bit audio is the demonstration of a jagged sine wave, like stairs. When we look at a file that has a resolution of 16 bits, we see an irregular line, but when we look at the same song in 24 bits, it seems to be a practically smooth line, with better definition. It is a basic visual illustration, but depending on the person’s knowledge of the subject, he can be easily fooled.

Why use 24-bit or more audio files?

The utility of using a high-level bit depth applies to studios, because with each filter and conversion that is applied, the background noise increases. This increase in noise occurs due to the insertion of a new wave, as explained above. In other words, when using a higher bit depth level, the sound engineer prevents the original audio from generating noise by manipulating it for mixing and mastering.

However, remember that this will be more useful for audio production and not for the listener, as explained above.

conclusion
What will make the difference will be the balance between the sounds made in the mastering and not the bit depth itself, since the 16 bits of the CD are already more than enough for music listeners.

Multimedia formats: Digital audio

Sound is a continuous signal. To be stored with computer systems
it must be sampled, thus obtaining a digital signal.
The parameters that characterize the sampling are basically three:

 The sample rate
 Bit depth
 The number of channels
these parameters influence both the space occupied and the quality of the audio file
digital obtained.

Digital Audio

Sampling rate

The sampling frequency is the measurement expressed in Hertz (Hz) of the number
of times per second in which an analog signal is measured and stored
in digital form.

The higher the sampling rate, the more the sequence of the samples
digital will be close to that of the original analog waveform.
Low sampling rates limit the frequency range that is
can record, which in turn can generate a recording that
poorly reproduces the original sound.
Two sampling frequencies:
A. Low sampling rate,
which distorts the wave of the original sound
B. High sampling rate,
which perfectly reproduces the wave of
original sound
To reproduce a certain frequency, the sampling frequency
it must be at least double it (Nyquist theorem).
For example, audio CDs have a sampling rate of 44.100 Hz,
so they can reproduce frequencies up to 22.050 Hz, which are hardly found
beyond the limit of human perception of 20,000 Hz.
The following table shows the most common sampling rates for
digital audio.

Bit depth

The bit depth represents the number of bits used to store a
single digital sample.
When a sound wave is sampled, each sample is assigned
the amplitude value closest to the original wave amplitude. A depth
in high bits it provides as many amplitude values as possible, which results in a
greater dynamic range (the difference in decibels between the maximum volume that the component can sustain without
distort the waves and the background noise it produces), lower and higher background noise
fidelity.
For example if you use 8 bits you have 256 possible values (28
) that, being
relatively few, offer less sound quality than a
tape; if instead 16 bits per sample are used, 65536 values are obtained
possible (216).
The most common examples are the audio CD, recorded in 16 bit, and the DVD, which
supports up to 24 bit depth.

Compression formats

Hand in hand with the advent of digitalization, multimedia applications have
they are increasingly widespread until they become commonplace. One of
multimedia features is certainly the use of digital audio
vowel and sound. The biggest obstacle associated with digitizing audio is
the large size of the files that are produced, which puts them at
sector operators (especially those linked to the internet) the problem of
reduce the space occupied by the data to obtain the double advantage of:
 save in terms of memory occupation;
 save in terms of transfer time on the network.

For this reason, speaking of digitizing the audio, it is necessary to speak
also of data compression techniques. The compression techniques of the
data, of whatever nature they are, are divided into:
 lossless: compress data through a lossless process
of information that takes advantage of redundancies in data encoding
 lossy: compress data through a lossy process
of information that takes advantage of redundancies in the use of data.

Lossless formats

Lossless compression formats are more suitable for archiving rather than
to reproduction, since most of them require complete
decompression before they can be played.
One of the most common lossless compression formats is FLAC (Free Lossless Audio Codec).

Lossy formats

Lossy compression formats use compression algorithms capable of
drastically reduce the amount of data required to store a sound,
guaranteeing however an acceptable and faithful reproduction of the original file uncompressed.