Introduction to Acoustics

and ‘s’ in English text – may be assigned special,
short transmission symbols to reduce the average
data rate. Representative techniques which employ
this include arithmetic coding and Huffman coding.
6. Interchannel difference coding: if two or more
channels are used and are sufficiently similar, datarate
savings may be attained by sending sum and
difference information, or a variant thereof. The expectation
is that the difference values will be small,
and can be coded in fewer bits using technique (4),
above. In the case of stereo content, this approach is
sometimes referred to as mid/side (M/S) coding.
In addition to the techniques described above (and
others), a lossless coder may either directly code timedomain
PCM samples, or may instead use running
transforms and operate in the frequency domain. In the
latter case, a specialized bit-exact transform may be used
to guarantee that the final output is an exact clone of the
input.
A fully realized lossless coder is likely to use
a combination of techniques like those described above,
requiring a flexible and perhaps elaborate bit stream
syntax. The process of selecting which coding options
will be brought to bear on a given block of samples
is often not readily apparent from inspection or simple
calculation, so the encoder may be required to try an exhaustive
search of all possibilities for each block in order
to select the best option. Needless to say, this can make
for a rather slow-running encoder, but usually does not
affect the speed of the decoder.
As may be evident, the effectiveness of a lossless
coder is very much signal dependent: some signals can
be compressed considerably more than others, and some,
such as full-level white noise, basically cannot be losslessly
compressed at all. Typical compression ratios run
in the range of 2:1 to 3:1. Because lossless compression
is inherently a variable bitrate (VBR) coding technology,
it is not well suited to real-time streaming applications,
such as broadcast or fixed-speed digital tape.
One weakness of lossless coding, and indeed of lossy
coding as well, is that an error of even a single bit (in,
say, one of the control codes specifying which method
to use to unpack a block of data) can cause the loss of
significant audio data. Some care must be used in the design
of the bitstream to ensure that re-synchronization
of the decoder in the face of data errors is reliably possible
within an acceptably short period. More generally,
the complexity and low error tolerance of almost any
data-reduction algorithm raises the regrettable possibility
that digital records, audio and otherwise, may be lost
Audio and Electroacoustics 18.5 Digital Audio 773
to future generations unless care is taken to avoid data
errors, and to ensure that decoding algorithms are carefully
documented and preserved in full detail. This is
especially critical in the case of proprietary algorithms
owned and maintained by commercial entities, whose
long-term future operation may not be assured.
Perceptual/Lossy Audio Coding
While one might wish that lossless coding be used
exclusively for digital audio compression, its limited
performance and variable bitrate render it inappropriate
for a large number of coding applications. For moreaggressive
compression and acceptable performance
within the constraint of constant bit rate, one must resort
to the use of perceptual audio coding.
The goal of perceptual audio coding is to preserve
and convey all of the perceptual aspects of audio content,
without regard to preserving the signal literally, usually
employing the fewest bits possible. Recall that the data
rate for a standard audio CD was about 1.4 Mbit/s. As
this is written, the lowest data rate in commercial use for
conveying high-quality stereo audio is no higher than 48
Kbits/s, used by satellite radio and for Internet streaming,
a data-compression ratio on the order of 30:1 or
better.
How is this accomplished? For starters, the use
of lossless coding is not retained and incorporated in
overall lossy algorithms. Every packet of information
generated and reduced to its ultimate compactness by
any part of a perceptual coder is a candidate for further
reduction in size if one or more lossless techniques can
be brought to bear effectively.
Beyond that, the keys to high-efficiency perceptual
coding are to:
1. suppress any audio components not contributing to
the ultimate perception,
2. ensure that all the audible components are conveyed
with no alteration in perceived quality, while using
the minimum possible number of bits, and
3. employ, as much as possible, high-level abstractions
to describe audio signals in purely perceptual terms,
while retaining enough precision and detail to allow
the decoder to accurately reconstitute a signal
indistinguishable from the original encoder input
signal.
One fundamental building block that has almost always
been part of the foundation of perceptual coders is a digital
filter bank. This, of course, mirrors the functionality
of the basilar membrane; and the frequency-domain out-
Part E 18.5