Audio dithering

What is audio dithering?

Audio dithering is an audio processing technique that adds a noise-like signal to a digital audio signal before converting it to a lower data format. This is usually done to ensure the accuracy of the digital audio sampling to improve and minimize the effects of quantization errors. When digital audio signals are recorded or edited, they are quantized into discrete values ​​(samples). The higher the resolution of the audio format, the more discrete values ​​are available to describe the audio signal. This means greater accuracy. However, due to rounding errors and other factors, inevitable quantization errors can occur when converting the signal from a higher resolution to a lower resolution. In quiet passages, fewer bits are used to represent the waveform, leading to audible artifacts and distortions - the quantization errors. Therefore, particularly quiet signals benefit from the use of dithering. By adding dither signals with a specific noise spectrum, the quantization errors can be reduced to an imperceptible level. Audio dithering is therefore an important process when creating high-quality digital audio recordings, as otherwise signals will be surrounded by quantization noise - the noise that is generated when an analog signal is converted to digital.

What is quantization noise?

Quantization noise is noise that results from converting an analog signal to a digital signal. When an analog signal is converted to a digital signal, it is broken down into a series of discrete values ​​called quantization levels. Because the analog signal is continuous, it cannot be perfectly broken down into the discrete quantization levels. This introduces an error called quantization error, which can distort the signal. Quantization noise arises when the quantization error is combined with random noise. Noise can be minimized by dithering, which adds artificial noise to the signal. This can help spread the quantization error over a broader frequency distribution, thereby reducing quantization noise. Quantization noise can be audible, especially at low resolutions and bit depths. However, at higher resolutions and bit depths, quantization noise is typically less audible and can be further reduced through the use of noise reduction algorithms.

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What are quantization errors?

Quantization errors are errors that occur when digital Recording or processing of analog analog signals can occur. They are created when an analog signal is converted into discrete values ​​(samples) for digital storage or processing. Quantization breaks down the analog signal into discrete values ​​that are stored in a digital format. The resolution of the digital format, ie the number of discrete values ​​available, determines the accuracy with which the analog signal can be reproduced. If the analog signal is between two discrete values, it is rounded to the nearest discrete value. This rounding process results in an error that appears as quantization errors or rounding errors referred to as. The size of the quantization error depends on the resolution of the digital format and the accuracy of rounding. The higher the resolution of the format, the smaller the quantization error.

Why is high resolution good for music production?

Higher resolutions in digital audio playback typically relate to a higher sample rate and/or higher bit depth. The sample rate indicates how often an analog signal is sampled per second in order to generate a digital signal from it. A higher sample rate means the analog signal is sampled more frequently, resulting in greater accuracy. Typical sampling rates for audio CDs are 44,1 kHz, while high-resolution audio formats such as FLAC or MQA support higher sampling rates of up to 192 kHz or even higher. Bit depth refers to the number of bits used to represent a sample. A higher bit depth means more bits are available to represent the signal level. With a higher bit depth, the number of levels is larger, ie there are more discrete values ​​that the signal can take on. A higher bit depth therefore means that the dynamic Range of the signal can be larger, allowing for greater accuracy and clarity of the audio signal. Overall, higher sample rates and greater bit depths typically result in better sound quality and a more natural soundstage, especially in music that contains a lot of detail and nuance. However, higher resolutions also require more storage capacity and higher audio signal processing requirements, both for recording and playback.

Which dithering should be used when?

Choosing the right dithering depends on several factors, including the recording method, the type of audio signal, and the desired output format. There are different types of dithering, and each type has its specific uses and characteristics. Some of the most common types of dithering are
  • Rectangular Dither: This is the simplest form of dither and is commonly used at low resolutions. However, it is prone to audible artifacts and can be undesirable at higher resolutions. This type of dithering adds a uniform noise to a signal that hides the quantization error. The noise is kept in a certain range to minimize the distortion of the signal.
  • Triangular dither: This type of dither produces slightly more noise than rectangular dither, but also less distortion. Triangular dithering adds triangular noise to the signal that is less annoying to human hearing than rectangular dithering. The shape of the noise helps minimize signal distortion and can deliver better sound quality at higher bit depths.
  • Noise-shaping dithering: This type of dithering uses psychoacoustic models to minimize noise and reduce artifacts in higher frequency ranges. It is particularly effective at high resolutions and is often used when generating high-resolution audio formats. This type of dithering confines the noise to specific frequency ranges of the signal. The goal is to minimize the audible noise by spreading the noise to less sensitive frequency ranges of the signal.
  • Dynamic Dithering: Dynamic dithering adjusts the noise to the signal to achieve the best balance between noise and signal quality. To do this, the signal strength is measured and the noise is adjusted accordingly. This type of dithering can provide good sound quality at different signal strengths.
However, it is important to note that the choice of dithering also depends on the specific needs of the audio content and the playback device. An experienced audio engineer can usually recommend which dithering is best for a particular recording or playback.

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