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4. Digital Audio Theory · Concept 3 of 8

Quantization Noise

It is the tiny hiss caused by rounding each sound snapshot to the nearest available value.

Quantization Noise Rounding each sample to the nearest step leaves a tiny error = faint hiss steps = 2^bits true signal stored steps red gap = error (+/- 0.5 step) errors pile up = hiss heard as Noise floor by bit depth +1 bit = step half size = -6 dB noise MUSIC (signal) 8-bit floor ~ -48 dB (loud hiss) 16-bit ~ -96 dB 24-bit ~ -144 dB (capture here) dynamic range SQNR (dB) = 6.02 x N + 1.76 N = bits per sample & SQNR = signal-to-quantization-noise ratio More bits → smaller steps → lower hiss. Use dither on the final bounce.

Each sample rounds to the nearest step; the leftover gap (+/- half a step) stacks up as a constant hiss whose level drops ~6 dB per bit.

What it is

Faint background fuzz caused by rounding each digital sample to the nearest available step value.

Key facts

How it works

  1. A mic signal is sampled thousands of times per second (e.g. 44,100 Hz).
  2. Each sample's loudness is measured against a fixed ladder of allowed values.
  3. The true value almost never lands on a step, so it gets rounded to the nearest one.
  4. That rounding gap (+/- 0.5 step) is the quantization error for that sample.
  5. Millions of tiny errors stack up over time and are heard as a faint constant hiss.
  6. More bits = many more steps = smaller gaps = much quieter, less audible noise.

Real examples

How it helps in live sound

Everyday analogy

Like a ruler marked only in whole centimetres: every measurement gets nudged to the nearest line, so it is never truly exact and the little errors pile up.

Watch out

Myth: 'more bits = higher resolution / better highs.' Truth: bit depth only sets the noise floor and dynamic range; sample rate sets frequency range. Extra bits lower hiss, they don't add highs.

Fun fact

Counterintuitively, adding a tiny bit of random noise (dither) BEFORE rounding makes the result sound cleaner: it trades harsh quantization distortion for a smooth, low hiss your ear ignores.

Key takeaways

  • Quantization noise = rounding error from snapping samples to fixed steps.
  • Each extra bit lowers the noise floor by ~6 dB (SQNR = 6.02N + 1.76 dB).
  • 16-bit ~ 96 dB range, 24-bit ~ 144 dB; capture at 24-bit.
  • Worst on quiet, exposed passages; buried under loud music.
  • Dither hides it as smooth hiss instead of ugly distortion.
  • Aim peaks at -18 to -12 dBFS to stay well above the noise.
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