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 processed, 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, unavoidable quantization errors may occur when converting the signal from a higher resolution to a lower resolution. In quiet areas, fewer bits are used to represent the waveform, resulting in audible artifacts and distortions - quantization errors. Therefore, particularly quiet signals benefit from 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, otherwise signals will be in quantization noise - i.e. the noise that is generated when analog signals are converted into digital ones.
What is quantization noise?
Quantization noise is noise created when an analog signal is converted into a digital signal. When an analog signal is converted to a digital signal, it is divided into a series of discrete values called quantization levels. Since the analog signal is continuous, it cannot be perfectly divided into the discrete quantization levels. This creates an error called quantization error, which can lead to distortion of the signal.
Quantization noise occurs when the quantization error is combined with random noise. Noise can be minimized through dithering by adding artificial noise to the signal. This can help spread the quantization error over a wider frequency distribution, thereby reducing quantization noise.
Quantization noise can be particularly audible at low resolutions and bit depths. However, at higher resolutions and bit depths, quantization noise is typically less audible and can be further reduced by using noise reduction algorithms.
Audio dithering from the pros! We make all your signals audible
What are quantization errors?
Quantization errors are errors that occur when digital Recording or processing of analog analog signals. They arise when an analog signal is converted into discrete values (sample values) for digital storage or processing.
Quantization involves breaking down the analog signal into discrete values that are stored in a digital format. The resolution of the digital format, i.e. 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 known 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 rounding accuracy. 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 typically refer to a higher sample rate and/or a higher bit depth.
The sample rate indicates how often an analog signal is sampled per second to generate a digital signal.
A higher sampling rate means that the analog signal is sampled more frequently, resulting in greater accuracy. Typical sample rates for audio CDs are 44,1 kHz, while high-resolution audio formats such as FLAC or MQA support higher sample 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 that more bits are available to represent the signal level. With a higher bit depth, the number of stages is larger, meaning 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 larger bit depths typically result in better sound quality and a more natural sound image, especially for music that contains a lot of detail and nuance. However, higher resolutions also require more storage capacity and higher audio signal processing requirements, both during recording and playback.
Analog sound for your tracks?
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 dithering: This is the simplest form of dithering and is often used at low resolutions. However, it is prone to audible artifacts and may be undesirable at higher resolutions. This type of dithering adds uniform noise to a signal that hides the quantization error. The noise is kept within a certain range to minimize distortion of the signal.
- Triangular dithering: This type of dithering produces slightly more noise than rectangular dithering, but also less distortion. Triangular dithering adds triangular noise to the signal, which is less annoying to human hearing than rectangular dithering. The shape of the noise helps minimize distortion of the signal 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 in producing high-resolution audio formats. With this type of dithering, the noise is limited to certain frequency ranges of the signal. The goal is to minimize audible noise by spreading the noise into less sensitive frequency ranges of the signal.
- Dynamic dithering: Dynamic dithering adjusts the noise to the signal to achieve an optimal ratio 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.
