MANUAL OF ANALOGUE SOUND RESTORATION ... - British Library

Alternatively it may be generated by a random-number algorithm in the digital domain.
Such “dither” will completely eliminate this distortion, at the cost of a very faint steady
hiss being added. The current debate is about methods of reducing, or perhaps making
deliberate use of, this additional hiss.
Today the normal practice is to add “triangular probability distribution” noise,
which is preferable to the “rectangular probability distribution” of earlier days, because
you don’t hear the hiss vary with signal volume (an effect called “modulation noise”).
Regrettably, many “sound cards” for computers still use rectangular probability
distribution noise, illustrating the gulf which can exist between digital engineers and
analogue ones! It also illustrates why you must be aware of basic principles on both sides
of the fence.
Even with triangular probability distribution noise, in the past few years this
strategy has been re-examined. There are now several processes which claim to make the
hiss less audible to human listeners while simultaneously avoiding quantisation distortion
and modulation noise. These processes have different starting-points. For example, some
are for studio recordings with very low background noise (at the “twenty-bit level”) so
they will sound better when configured for sixteen-bit Compact Discs. Such hiss might
subjectively be fifteen decibels quieter, yet have an un-natural quality; so other processes
aim for a more “benign” hiss. A process suggested by Philips adds something which
sounds like hiss, but which actually comprises pseudo-random digits which carry useful
information. Another process (called “auto-dither”) adds pseudo-random digits which can
be subtracted upon replay, thereby making such dither totally inaudible, although it will
still be reproduced on an ordinary machine. Personally I advocate good old triangular
probability distribution noise for the somewhat esoteric reason that it’s always possible to
say where the “original sound” stopped and the “destination medium” starts.
All this is largely irrelevant to archivists transferring analogue recordings to digital,
except that you should not forget “non-human” applications such as wildlife recording.
There is also a risk of unsuspected cumulative build-ups over several generations of digital
processing, and unexpected side-effects (or actual loss of information) if some types of
processing are carried out upon the results.
If you put a recording through a digital process which drops the volume of some or
all of the recording so that the remaining hiss (whether “dither” or “natural”) is less than
the least-significant bit, it will have to be “re-dithered.” We should also perform redithering
if the resulting sounds involve fractions of a bit, rather than integers; I am told
that a gain change of a fraction of a decibel causes endless side-effects! One version of a
widely-used process called The Fast Fourier Transform splits the frequency-range into
2048 slices, so the noise energy may be reduced by a factor of 2048 (or more) in some
slices. If this falls below the least-significant bit, quantisation distortion will begin to affect
the wanted signal.
In my personal view, the best way of avoiding these troubles is to use 24-bit
samples during the generation of any archive and objective copies which need digital
signal processing. The results can then be reduced to 16-bits for storage, and the sideeffects
tailored at that stage. Practical 24-bit encoders do not yet exist, because they have
insufficiently low background noise; but this is exactly why they solve the difficulty.
Provided digital processing takes place in the 24-bit domain, the side-effects will be at
least 48 decibels lower than with 16-bit encoding, and quantisation distortion will hardly
ever come into the picture at all.
On the other hand, if 16-bit processing is used, the operator must move his sound
from one process to the next without re-dithering it unnecessarily (to avoid building up
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