Introduction to Acoustics

774 Part E Music, Speech, Electroacoustics
Part E 18.5
put signals are most commonly used for both the analysis
sections of the coder and the signal path. Indeed, the
fundamental data conveyed by most perceptual coders
is not PCM time-domain data, but quantized frequencydomain
information from which the decoder eventually
produces PCM output by way of a synthesis filter bank.
The most commonly used digital filter bank is a variant
of the FFT called the time-domain alias cancellation
(TDAC) transform, developed by Princen and Bradley
in 1986 [18.69,70]. This transform has the highly desirable
property of being critically sampled, meaning that it
produces exactly the same number of output frequencydomain
samples as there are input PCM samples. There
is also a companion inverse TDAC transform for producing
output PCM from a set of decoded frequency-domain
input samples.
In operation, PCM samples input to the encoder
are divided into regular blocks of some predetermined
length, and each block is transformed to the frequency
domain, conveyed to the decoder, reconstituted
as a block of PCM samples, and the successive blocks
strung together, often in an overlapping manner, to
recover the final outputs. This process is sometimes
described as block-oriented processing using running
transforms. The practice of coding an entire block of
samples as a single entity facilitates data rates of less than
one bit per original audio sample. One downside of block
processing is that events which occupy a small fraction
of a block, like a sharp transient, may become smeared
across a range of frequencies, consuming a large number
of bits. A number of techniques have evolved to deal
with this situation, most commonly the use of block
switching, wherein such short events are detected (by,
for example, a transient detector routine), and the block
size is temporarily shortened to more closely isolate the
transient within the shortened block.
The filter-bank output is of direct use in pursuit of
the first two perceptual coding techniques listed above,
principally by deriving the magnitude of the frequencydomain
signals as a function of frequency to obtain
a discrete approximation to the power spectral density
(PSD) of the signal block. This in turn is processed by
a routine implementing a perceptual model of human
hearing to derive a masking curve, which specifies the
threshold of hearing as a function of frequency for that
signal block. Any spectral component falling below the
masking curve will be inaudible, so need not be coded,
as per the first listed coding technique. The remaining
spectral components must be preserved if audible
alteration is to be avoided, but the quantization precision
is only that which is required to render the level of
the quantization noise below the masking curve. Instead
of the 120 dB/20 bit range one might require for PCM
audio, the instantaneous masking range is more often
on the order of 20–30 dB, about 4–5 bits per sample,
assuming 6 dB per bit SNR. Thus, between suppression
of inaudible components and dynamic quantization
of audible components, the data rate can be expected
to be reduced to something less than 4 bits per sample.
Of course, an effective bit-stream syntax protocol
must be devised to signal these conditions efficiently
to the decoder, and considerable ingenuity has been
brought to bear on that issue to ensure the requirement
is met.
Notable lossy audio coders based on these principles
include AC-3,MP3,DTS,WMA,Ogg,andAAC.These
have been instrumental enablers of such technologies as
portable music players, DVD’s, digital soundtracks on
35 mm film, and satellite radio.
It should be noted that perceptual coding is much
more compatible with constant-bit-rate operation than
is lossless coding, for as the complexity of a signal increases,
which might otherwise increase the required
data rate, the masking afforded by that signal also
increases, reducing the average quantization accuracy
required, thereby holding the required data rate to a more
nearly constant rate. In effect, the human auditory system
can only absorb so much information per unit time,
so as long as the coder accurately models that behavior,
the required data rate should be largely constant. Of
course, very simple signals, like silence, are not likely
to require the same data rate as more complex signals,
in which case a constant-bitrate coder may simply use
far more than the minimum required data rate in order to
maintain a constant transmission rate. Some coders can
defer use of bits in the presence of simple signals, savingtheminabit
bucket until needed by a more complex
signal.
The third listed technique used in perceptual coding,
the application of higher-level abstractions to describe
the signal, is much more general and open-ended; and is
still an area of active investigation. It can be something
as simple as using a single PSD curve to approximate
the actual PSD curves of several successive transform
blocks, or using decoder-generated noise in place of
actually transmitting noise-like signals. More abstract
approaches may fall under the heading of parametric
coding.
One notable example of parametric coding is bandwidth
extension, in which the entire high-frequency end
of the spectrum is suppressed by the encoder, and is reconstituted
by the decoder from analysis of the harmonic