Audio bit depth
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.
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.
