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Music Technology 101: Dithering Explained (1/2) - Quantization Noise 

MangoldProject
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In this two-part video tutorial I will explain dithering from the ground up. For your convenience, here are the links to the two parts:
Part 1: • Music Technology 101: ...
Part 2: • Music Technology 101: ...
You do not need any special background in signal processing, audio or dithering to follow the current videos. However, you should know what bit depth means. If you don't, fear not! Just watch my short video tutorial about bit-depth and sampling rates right here:
• Music Technology 101: ...
What's in Part 1: Dithering is all about getting rid of quantization noise. What is quantization noise? Glad you've asked, because that's exactly what we're going to cover in the first part! Shortly put, quantization noise is the noise introduced whenever we reduce the bit depth of our signal. For example, most audio is recorded using 24 bits of resolution, but modern audio CDs only have 16 bits of resolution, implying that a reduction in bit depth must be applied. This reduction will introduce some artifacts known as quantization error, or quantization noise. This "noise" will have some jarring, unpleasant frequency components which we'd like to get rid of.
What's in Part 2: In the second part we will cover dithering. To "dither" a signal means to add some form of random noise to it because lowering its bit depth. This dither noise has a beneficial effect: while it doesn't eliminate quantization noise, it gives it a more random, "white" nature which is less disturbing to the listener. When the amount of white noise equals approximately 1 bit in magnitude, the quantization error becomes a lot like white noise. This is because quantization involves rounding the input signal either up or down. When the noise becomes on the order of 1 bit, the rounding becomes random, and therefore the quantization error becomes random as well.
DITHERING TYPES
Dithering requires that we add random noise to our signal before downsampling. This noise should have a flat spectrum - in other words, be white. However, there is more than one way to generate white random noise. Probably the easiest and most efficient way is to use what's known as a triangular probability distribution function, or TPDF. You might have seen these initials in your dithering plugin. This is an excellent way to efficiently dither. Although we won't discuss the heavy mathematical theory of dithering in this video, I'll just mention that TPDF white noise decouples the first and second moments of the quantization noise.
Another option consists of using noise with a non-flat spectrum. For example, you'd might add noise that has more high-frequency components, such as Blue Noise. This is referred to as shaped noise, shaped noise dithering, or colored dithering. What this tries to do is force the dithered quantization noise to occupy higher frequencies that are outside the human audio range. Once again, personal experimentation is key to deciding whether you want to use colored dithering or not, but this is truly a very fine point. You will be fine if you just stick to TPDF. However, a word of caution: only apply colored dithering at the FINAL stage of your processing. If you need to dither audio at some point DURING mixing, use TPDF. This is because subsequent processing of the audio can cause the colored noise to creep into the audible listening range and create nasty artifacts. So: Use TPDF at all stages before mixing, and use TPDF or colored dithering during the final mixdown.
LINKS OF INTEREST
Here is a wonderful guide to dithering written in 2002 by Nika Aldrich, targeted at the audio engineer:
www.users.qwest...
This is truly geared towards the audio enthusiast and does not go into any math. It is heavily illustrated and references industry standard plugins such as Apogee's UV22.
Wikipedia's entry on dithering: en.wikipedia.or...
My Other Videos
My RU-vid channel has many other video tutorials covering various topics in both audio and music, mostly geared towards piano playing. Here are a few examples:
Bit depth and sample rate explained: • Music Technology 101: ...
Song writing Tips and Tricks - Rhythmic Doubling: • Free Songwriting Secre...
Reading Sheet Music for Beginners: • Reading Sheet Music fo...
The 2-5-1 Harmonic Progression Tutorial: • Harmony 101: The 2-5-1...
Playing Left hand Piano Arpeggios: • Best Free Piano Lesson...
An Exercise for Developing Piano Right-Hand Technique: • Developing Piano Techn...

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28 авг 2024

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Комментарии : 28   
@peterjr7
@peterjr7 3 года назад
OMG so well explained!!!! thank you very much!!!
@Lexyvil
@Lexyvil 2 года назад
That's so interesting! So in the Quantized signal, you can hear both the original and the noise at the same time. I'm guessing that's how hearing multiple sounds work in real life. Thanks for the image example too, it helps visualize it more.
@iBrade
@iBrade 10 лет назад
Only 1 minute in and i find it more interesting than what my lecture teaches me.
@alexkozarmedia
@alexkozarmedia 10 лет назад
Great explanations here. It's very interesting to see the details behind quantisation noise
@MangoldProject
@MangoldProject 10 лет назад
Glad you liked it. I find that hands-on experimentation is usually the best way of really "knowing" something, but often knowing the theory tells you how to experiment, since there are so many possibilities.
@josephjwoods66
@josephjwoods66 8 лет назад
Great video, concise with excellent examples on to part 2
@alisaljic
@alisaljic 10 лет назад
Thank you. Once again, very concise and understandable.
@samworskett
@samworskett 9 лет назад
Excellent video - perfectly explained. Thanks!
@mittluk
@mittluk 8 лет назад
great video! absolutly helpful!
@HellaHipHop
@HellaHipHop 7 лет назад
the dark arts. ahhhh my love
@williamrussotto8702
@williamrussotto8702 7 лет назад
Brilliant explanation
@2592Thomas
@2592Thomas 3 года назад
thanks a lot!
@575garden
@575garden 5 лет назад
fantastic video
@MikePreset
@MikePreset 8 лет назад
that was so clearly explained ..Thank you
@MangoldProject
@MangoldProject 8 лет назад
You're welcome Mike.
@sticksquash
@sticksquash 10 лет назад
Don't most players have some sort of interpolation on bit depth and sample rate to make it sound more smoother, or curve it as opposed to say connecting the dots (linear) or using the nearest neighbor? Probably through a cubic interpolation? It would at least make it resemble a sinusoidal but might make more complex waveforms more muddy.
@MangoldProject
@MangoldProject 9 лет назад
That's a good question. I don't know the answer to that. One thing's for sure: *some* sort of "interpolation" is used simply by turning the digital signal into a continuous analog voltage signal. However this is not what you were talking about.
@AndrewJohnClive
@AndrewJohnClive 9 лет назад
Thanks Buddy. Excellent!
@MangoldProject
@MangoldProject 9 лет назад
Thanks for watching!
@compiutershick1
@compiutershick1 4 года назад
Thank you!
@Willton25091990
@Willton25091990 8 лет назад
Love it!!
@pierrejeanes
@pierrejeanes 8 месяцев назад
But sir i just don't get it, an error due to low depth its simply a slightly different frequency and amplitude of the original but when played it sounds like noise
@MangoldProject
@MangoldProject 8 месяцев назад
Not sure I understood your question.
@redirishmanxlt
@redirishmanxlt 10 лет назад
If I render a track to WAV using 48khz and 24bit, would there be any need for dithering? What I'm trying do is render an entire track to audio, and then master it with dithering.
@MangoldProject
@MangoldProject 10 лет назад
Ideally, you should dither whenever you reduce the bit depth of your audio. So, whether or not you'd need dithering would depend on whether your source material is at a higher bit depth than 24 bits.
@abmunguia
@abmunguia 9 лет назад
This is real altruism.
@MangoldProject
@MangoldProject 9 лет назад
Thanks man. I really appreciate the comment.
@GingerBagels
@GingerBagels 8 лет назад
I just don't get it...