I’d really appreciate a little tech tip on Dither.
I tried to get my head around the following piece but i think i need someone telling me in layman terms via audio/visual representation.
What is dither?
To dither means to add noise to our audio signal. Yes, we add noise on purpose, and it is a good thing.
How can adding noise be a good thing??!!!
We add noise to make a trade. We trade a little low-level hiss for a big reduction in distortion. It’s a good trade, and one that our ears like.
The problem
The problem results from something Nyquist didn’t mention about a real-world implementation—the shortcoming of using a fixed number of bits (16, for instance) to accurately represent our sample points. The technical term for this is “finite wordlength effects”.
At first blush, 16 bits sounds pretty good—96 dB dynamic range, we’re told. And it is pretty good—if you use all of it all of the time. We can’t. We don’t listen to full-amplitude (“full code”) sine waves, for instance. If you adjust the recording to allow for peaks that hit the full sixteen bits, that means much of the music is recorded at a much lower volume—using fewer bits.
In fact, if you think about the quietest sine wave you can play back this way, you’ll realize it’s one bit in amplitude—and therefore plays back as a square wave. Yikes! Talk about distortion. It’s easy to see that the lower the signal levels, the higher the relative distortion. Equally disturbing, components smaller than the level of one bit simply won’t be recorded at all.
This is where dither comes in. If we add a little noise to the recording process… well, first, an analogy…
An analogy
Try this experiment yourself, right now. Spread your fingers and hold them up a few inches in front of one eye, and close the other. Try to read this text. Your fingers will certainly block portions of the text (the smaller the text, the more you’ll be missing), making reading difficult.
Wag your hand back and forth (to and fro!) quickly. You’ll be able to read all of the text easily. You’ll see the blur of your hand in front of the text, but definitely an improvement over what we had before.
The blur is analogous to the noise we add in dithering. We trade off a little added noise for a much better picture of what’s underneath.
Back to audio
For audio, dithering is done by adding noise of a level less than the least-significant bit before rounding to 16 bits. The added noise has the effect of spreading the many short-term errors across the audio spectrum as broadband noise. We can make small improvements to this dithering algorithm (such as shaping the noise to areas where it’s less objectionable), but the process remains simply one of adding the minimal amount of noise necessary to do the job.
An added bonus
Besides reducing the distortion of the low-level components, dither let’s us hear components below the level of our least-significant bit! How? By jiggling a signal that’s not large enough to cause a bit transition on its own, the added noise pushes it over the transition point for an amount statistically proportional to its actual amplitude level. Our ears and brain, skilled at separating such a signal from the background noise, does the rest. Just as we can follow a conversation in a much louder room, we can pull the weak signal out of the noise.
Going back to our hand-waving analogy, you can demonstrate this principle for yourself. View a large text character (or an object around you), and view it by looking through a gap between your fingers. Close the gap so that you can see only a portion of the character in any one position. Now jiggle your hand back and forth. Even though you can’t see the entire character at any one instant, your brain will average and assemble the different views to put the characters together. It may look fuzzy, but you can easily discern it.
When do we need to dither?
At its most basic level, dither is required only when reducing the number of bits used to represent a signal. So, an obvious need for dither is when you reduce a 16-bit sound file to eight bits. Instead of truncating or rounding to fit the samples into the reduced word size—creating harmonic and intermodulation distortion—the added dither spreads the error out over time, as broadband noise.
But there are less obvious reductions in wordlength happening all the time as you work with digital audio. First, when you record, you are reducing from an essentially unlimited wordlength (an analog signal) to 16 bits. You must dither at this point, but don’t bother to check the specs on your equipment—noise in your recording chain typically is more than adequate to perform the dithering!
At this point, if you simply played back what you recorded, you wouldn’t need to dither again. However, almost any kind of signal processing causes a reduction of bits, and prompts the need to dither. The culprit is multiplication. When you multiply two 16-bit values, you get a 32-bit value. You can’t simply discard or round with the extra bits—you must dither.
Any for of gain change uses multiplication, you need to dither. This means not only when the volume level of a digital audio track is something other than 100%, but also when you mix multiple tracks together (which generally has an implied level scaling built in). And any form of filtering uses multiplication and requires dithering afterwards.
The process of normalizing—adjust a sound file’s level so that its peaks are at full level—is also a gain change and requires dithering. In fact, some people normalize a signal after every digital edit they make, mistakenly thinking they are maximizing the signal-to-noise ratio. In fact, they are doing nothing except increasing noise and distortion, since the noise level is “normalized” along with the signal and the signal has to be redithered or suffer more distortion. Don’t normalize until you’re done processing and wish to adjust the level to full code.
Your digital audio editing software should know this and dither automatically when appropriate. One caveat is that dithering does require some computational power itself, so the software is more likely to take shortcuts when doing “real-time” processing as compared to processing a file in a non-real-time manner. So, an applications that presents you with a live on-screen mixer with live effects for real-time control of digital track mixdown is likely to skimp in this area, whereas an application that must complete its process before you can hear the result doesn’t need to.
Is that the best we can do?
If we use high enough resolution, dither becomes unnecessary. For audio, this means 24 bits (or 32-bit floating point). At that point, the dynamic range is such that the least-significant bit is equivalent to the amplitude of noise at the atomic level—no sense going further. Audio digital signal processors usually work at this resolution, so they can do their intermediate calculations without fear of significant errors, and dither only when its time to deliver the result as 16-bit values. (That’s OK, since there aren’t any 24-bit accurate A/D convertors to record with. We could compute a 24-bit accurate waveform, but there are no 24-bit D/A convertors to play it back on either! Still, a 24-bit system would be great because we could do all the processing and editing we want, then dither only when we want to hear it.)
+1 for a video
Also if it could explain so i could fully understand 44.1 hz and 96 hz and it’s effects with 24bit and 16bit etc.
Thankyouuuu 
In laymens terms, you are adding noises(white/pink tones) to help bring/push out other sounds. This is where superior audio engineeing usually comes into play. This isn’t usually messed with by anyone other than a master engineer working on live works. This is the actaul reason why most computer recording software comes with pink and white noise tools. Think of it like this, forget the math part, it will just mess with you:
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Analogy: You have a steak just sitting on the table. It looks good, you can see it, you can smell it, but it’s just there. Now you put that steak on a small white plate and hot damn! That thing now looks great and you can almost taste it! You haven’t really done anything other than trick the human mind into thinking around the fact that it’s just a steak. Same thing applies with adding different tones of white and pink noise. If you have a weak sound sitting at a certain frequency, you put a bit of noise behind it to bring it out of the mix, just like the steak on the plate. Typically the noise that you introduce will be inaudible to the human ear. The tricky part is when you dither too much, you start to lose the overall feel of the mix. Kind of like over eq’ing.
Hope this helped! Sorry I haven’t been around for a while guys! Been busy as you know what!!!
Raymond
edit# this is about as laymen as it can get without getting involved in sound reduction algo’s and whatnot. Dither is ALL MATH. ALL.
edit2# this is based on manually doing things. F’all knows what Ableton does in this process. This is probably where scripting your own algo’s would come into play.
So you add white noise (whats pink noise?) to tracks? That doesnt really make any sense mate, how does adding inaudiable sound make it better??
[quote]raymondsar (9/9/2009)[hr]Analogy: You have a steak just sitting on the table. It looks good, you can see it, you can smell it, but it’s just there. Now you put that steak on a small white plate and hot damn! That thing now looks great and you can almost taste it! You haven’t really done anything other than trick the human mind into thinking around the fact that it’s just a steak.[/quote]
However, you forgot to mention that if you are overweight like me, you might need two plates…
I think I missed this one…
:hehe:
Think of dithering as an audio “sander”. You use it to smooth out edges and bring sounds out. The introduction of white/pink noise only tricks your ear into thinking the sound you are hearing is something else. IE, At bit 1 a low sine becomes a square. You use the noise to round out the square back into a sine. This doesn’t really occur though, it’s just dithering providing an audio illusion.
Pink Noise:
Pink noise is acoustical energy distributed uniformly by octave throughout the audio spectrum (the range of human hearing, approximately 20 Hz to 20 kHz). Most people perceive pink noise as having uniform spectral power density – the same apparent loudness at all frequencies. In pink noise, the total sound power in each octave is the same as the total sound power in the octave immediately above or below it. An octave is a band whose highest frequency is exactly twice its lowest frequency.
So-called white noise contains sound power distributed uniformly in absolute terms. True white noise sounds like there is more treble than bass because the human ear/mind interprets sound in terms of octaves, not in terms of absolute frequency. Any given octave represents a frequency band twice as large, in arithmetic terms, as the one below it. For example, the octave from 100-200 Hz is 100 Hz wide, the next octave (200-400 Hz) is 200 Hz wide, the octave above that (400-800 Hz) is 400 Hz wide, and so on.
Pink noise can be obtained from white noise by means of a low-pass filter designed so the output spectral power density (that is, the sound power contained within a narrow frequency band of a certain fixed width, such as 1 Hz) drops by 50 percent with each octave as the absolute frequency rises. Pink noise can also be directly generated by a computer-controlled acoustic synthesizer.
The terms “pink” and “white” come from optics. The visual color pink has greater spectral power density at the longer optical wavelengths (lower frequencies, near the red end of the visible spectrum) than at the shorter optical wavelengths (higher frequencies, near the violet end of the visible spectrum). Some engineers talk about “brown noise,” which is similar to pink noise except that the spectral power density decreases even more rapidly with increasing frequency.
White, pink, and brown noise can be generated by an acoustic synthesizer to produce sound effects mimicking surf on a beach, a high wind through trees, a rocket taking off, and other phenomena. White and pink noise are used by audio engineers to test and adjust sound recording and reproduction equipment.
Raymond
Thanks raymond, superstar.
I still don’t really fully understand the logistics and technical behind how adding sound, makes sound clearer, but at the same time i feel that there is probably little chance i’d ever come across an instance where i’d need to fully understand this. I’ve at no point as of yet had to add any pink/white noise to my tracks to acheive the dither, but then i’m no pro so maybe it is something i need to do at times?
I have never seen this applied to anything other than LIVE recordings of instruments. Dithering is mostly used in conjunction with limiters in recording arts. When you limit something it drops all levels so they stay uniform without peaking, pushing some of your sounds down to the first bit distorting them. That’s when you would dither. Best way to think of it. Dithering is the exact opposite of bit crushing. Dither you fix, crush, well, that 's self explanatory! Without you guys being bona fide engineers it would be hard to explain how bits and sample rates work. I have yet to come across an easy way to explain it other than Hi Resolution. Hense once you get up into the 24bit range, there’s enough bits for all the sounds to fit, so you don’t need to dither(there’s always an exception). You only need to dither to make them fit in the bit range and be audible without distortion.Like I said, it’s all math, and this is definitely a science! If you can learn to count in bits, by 8’s, and you can understand the form and function algos that come with sound creation, then you will know exactly what, when, and where to dither. The majority of digital software dithers automatically making anything you do redundant. A typical low level feedback on an analog rig will provide enough background white noise to dither for you as well. Honestly, I can’t really think of any reason that any electronic artist working from software would need to do this. Doesn’t mean that there shouldn’t be a tutorial though!!! I think crazy things like this definitely have a place in ALL music.
Raymond
edit: I suppose that people that thrive on the lo fi 8bit sounds like fidget house might have a more experimental use. But they typically use bitcrushers to achieve what they need, and definitely aren’t trying to “clean” the sound up as its duurrrrttttyyyy for a reason!
holy sh*t those are some long posts