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Though any number of quantization levels is possible, common word lengths are 8-bit (256 levels), 16-bit (65,536 levels) and 24-bit (16.8 million levels). Quantizing a sequence of numbers produces a sequence of quantization errors which is sometimes modeled as an additive random signal called quantization noise because of its stochastic ...
The purpose of quantization in music processing is to provide a more beat-accurate timing of sounds. [2] Quantization is frequently applied to a record of MIDI notes created by the use of a musical keyboard or drum machine. Additionally, the phrase "pitch quantization" can refer to pitch correction used in audio production, such as using Auto-Tune.
The noise introduced by quantization error, including rounding errors and loss of precision introduced during audio processing, can be mitigated by adding a small amount of random noise, called dither, to the signal before quantizing.
Noise shaping works by putting quantization noise in a feedback loop designed to filter the noise as desired. Low-pass boxcar filter example For example, consider the ...
Version 2 of Studio One was announced on 17 October 2011, [13] [14] and released on 31 October 2011 (alongside the 2.0.2 update). [15] This release of the software introduced multiple enhancements, including integration with Celemony Melodyne, transient detection & quantization, groove extraction, multi-track comping, folder tracks, multi-track MIDI editing, an updated browser, and new plug-ins.
The Signal-to-quantization-noise ratio is a multiple of the bit depth. Audio CDs use a bit depth of 16-bits, while DVD-Video and Blu-ray discs can use 24-bit audio. The maximum dynamic range of a 16-bit system is about 96 dB, [ 10 ] while for 24 bit it is about 144 dB.
Companded quantization is the combination of three functional building blocks – namely, a (continuous-domain) signal dynamic range compressor, a limited-range uniform quantizer, and a (continuous-domain) signal dynamic range expander that inverts the compressor function. This type of quantization is frequently used in telephony systems.
As a form of vector quantization, PVQ defines a codebook of M quantization points, each of which is assigned an integer codeword from 0 to M−1. The goal of the encoder is to find the codeword of the closest vector, which the decoder must decode back into a vector.