Title of Invention

METHOD AND APPARATUS FOR GENERATING AN OUTPUT SIGNAL

Abstract Analysis and synthesis filter banks (3) such as those used in audio and video coding systems are each implemented by a hybrid transform that comprises a primary transform (43) in cascade with one or more secondary transforms (45a, 45b). The primary transforms for the filter banks implement an analysis/synthesis system in which time-domain aliasing artifacts are cancelled. The secondary transforms (45a, 45b), which are in cascade with the primary transforms (43), are applied to blocks of transform coefficients. The length of the blocks is varied to adapt the time resolution of the analysis and synthesis filter banks.
Full Text

TECHNICAL FIELD
The present invention pertains generally to signal analysis and synthesis filter banks
such as those that may be used in audio and video coding systems. More particularly, the
present invention pertains to analysis and synthesis filter banks implemented by a cascade
of block transforms that are able to adapt the time and frequency resolutions of the filter
banks.
BACKGROUND ART
Coding systems are often used to reduce the amount of information required to
adequately represent a source signal. By reducing information capacity requirements, a
signal representation can be transmitted over channels having lower bandwidth or stored
on media using less space. Coding can reduce the information capacity requirements of a
source signal by removing either redundant components or irrelevant components in the
signal. So called perceptual coding methods and systems often use filter banks to reduce
redundancy by decorrelating a source signal using a basis set of spectral components, and
reduce irrelevancy by adaptive quantization of the spectral components according to
psycho-perceptual criteria.
Many perceptual coding systems implement the filter banks by block transforms.
In an audio coding system, for example, a source audio signal, which is represented by
time segments or blocks of time-domain samples, is transformed into sets of frequency-
domain coefficients representing the spectral content of the source signal. The length of
the segments establishes both the time resolution and the frequency resolution of the filter
bank. Time resolution increases as the segment length decreases. Frequency resolution
increases as the segment length increases. Because of this relationship, the choice of
segment length imposes a trade off between the time and frequency resolution of a block
transform filter bank. 1
No single choice of segment length can provide an optimum trade off between
resolutions for all of the source signal conditions that are encountered by typical coding
systems. Slowly varying or stationary source signals generally can be encoded more
efficiently if the filter bank has a higher frequency resolution, which can be provided if a

longer segment length is used. Rapidly varying or highly non-stationary source signals
generally can be encoded more efficiently if the filter bank has a higher time resolution,
which can be provided if a shorter segment length is used. By adapting the segment
length in response to changing source signal conditions, a block transform filter bank can
optimize the tradeoff between its time and frequency resolution.
A large variety of transforms may be used to implement filter banks in audio
coding systems, for example, but a particular Modified Discrete Cosine Transform
(MDCT) is widely used because it has several very attractive properties for audio coding
including the ability to provide critical sampling while allowing adjacent source signal
segments to overlap one another. The MDCT is also attractive because it is able to
remove substantially all redundant components in a source signal that is substantially
stationary within a segment. Proper operation of the MDCT filter bank requires the use of
overlapped source-signal segments and window functions that satisfy certain criteria
described in Princen et al., "Subband/Transform Coding Using Filter Bank Designs Based
on Time Domain Aliasing Cancellation," Proc. of the 1987 International Conference on
Acoustics, Speech and Signal Processing (ICASSP), May 1987, pp. 2161-64.
Unfortunately, it is difficult to adapt the time and frequency resolution of MDCT filter
banks in response to signal conditions because of the requirements imposed on the
window functions that must be applied to overlapping source signal segments.
One known technique sometimes referred to as "window switching" is able to
adapt the time resolution of a MDCT filter bank by adaptively switching between two
different window functions in response to the detection of certain signal conditions such
as abrupt signal changes or amplitude transients. According to this technique, which is
described in U.S. patent 5,214,742 by Edler, issued May 25, 1993, segment lengths are
not changed but the time resolution is adapted by switching between different window
function shapes to reduce the number of non-zero samples in each segment that are
transformed by the filter bank. Unfortunately, this technique does not adapt the frequency
resolution of the filter bank and the frequency selectivity of the filter bank is seriously
degraded whenever the time resolution is reduced because the shape of the window
functions needed for window switching must be suboptimal to satisfy the requirements
for proper operation of the MDCT.
Another known technique sometimes referred to as "block switching" is similar to
the window-switching technique mentioned above in that it also switches between

different window function shapes, but the block-switching technique is able to adapt both
time and frequency resolutions of a MDCT filter bank by also adaptively switching
between two different segment lengths in response to the detection of certain signal
conditions such as abrupt signal changes or amplitude transients. This technique is used in
the Advanced Audio Coder (AAC), which is described in Bosi et al., "ISO/TEC MPEG-2
Advanced Audio Coding," J. Audio Eng. Soc, vol. 45, no. 10, October 1997, pp.789-814.
In AAC, a MDCT filter bank is applied to stationary source signal segments
having a length equal to 2048 samples and is applied to non-stationary source signal
segments having a length equal to 256 samples. Block switching is achieved in AAC by
using "long window functions" that are appropriate for the longer segments, "short
window functions" that are appropriate for the shorter segments, a "long-to-short bridging
window function" that allows switching from the longer segment length to the shorter
segment length, and a "short-to-long bridging window function" that allows switching
from the shorter segment length to the longer segment length. The two bridging window
functions allow switching between different segment length while satisfying the criteria
necessary for proper operation of the MDCT. A switch from a longer segment length to a
shorter segment length and back to the longer length is accomplished by applying the
MDCT to a long segment using the long-to-short bridging window function, applying the
MDCT to an integer multiple of eight short segments using the short window function,
and applying the MDCT to a long segment using the short-to-long bridging window
function. Immediately thereafter, the MDCT must be applied to a long segment but the
long window function may be used or the long-to-short bridging window function may be
used if another block switch is desired.
Although block switching does provide a way to adapt the time and frequency
resolution of a MDCT filter bank, it is not an ideal solution for several reasons. One
reason is that the frequency selectivity of the transform is degraded during a switch of
block lengths because the shape of the bridge window functions must be suboptimal to
allow segment-length switching and to satisfy requirements for proper operation of the
MDCT. Another reason is that a switch cannot occur at any arbitrary time. As explained
above, the MDCT must be applied to another long segment immediately after switching
to the longer segment length. An immediate switch to the shorter length is not possible.
This block switching technique also is not an ideal solution because the switching
mechanism provides only two segment lengths, which are not optimum for all signal

conditions. For example, the two segment lengths in AAC are not optimal because neither
the longer nor the shorter segment length in AAC is optimum for most speech signal
segments. The 2048-sample segments are usually too long for the non-stationary nature of
speech and the 256-sample segments are usually too short to remove redundant
components effectively. Furthermore, there are many stationary signals for which a
segment length longer than 2048 samples would be more optimum. As a result, the
performance of AAC is impaired by the limited ability of block switching to adapt the
time and frequency resolution of a MDCT filter bank.
Another form of block switching is used in coding systems that conform to the
Dolby Digital encoded bit stream standard. This coding standard, sometimes referred to
as AC-3, is described in the Advanced Television Systems Committee (ATSC) A/52A
document entitled "Revision A to Digital Audio Compression (AC-3) Standard"
published August 20, 2001. The form of block switching used in AC-3 coding systems
applies a MDCT to source signal segments of either 512 samples for stationary signals or
256 samples for non-stationary signals. The block switching technique used in AC-3
coding systems provides more flexibility in choosing when length switches are made.
Furthermore, coding performance is reasonably good for non-stationary source signals
like speech; however, the coding performance for signals that are more stationary is
limited by the relatively low frequency resolution provided by the longer segment.
Other techniques for adaptive control of the time and frequency resolution of a
MDCT filter bank are described in U.S. patent 5,394,473 by Davidson, which issued
February 28, 1995. Some of these techniques allow a MDCT filter bank to be applied to
segments of essentially any length using window functions that provide much a better
frequency response than is possible by other known techniques. Unfortunately, these
techniques must adapt the kernel or basis functions of the MDCT and are, therefore,
incompatible with existing bit stream standards like the AC-3 standard mentioned above.
These techniques are also computationally intensive.
DISCLOSURE OF INVENTION
What is needed is a more efficient and effective way to adapt the frequency
resolution of filter banks implemented by transforms like the MDCT. Preferably, the
solution should provide an implementation that simplifies its incorporation into systems
that are compatible with existing bit stream standards. This is achieved by using a hybrid-
transform filter bank that may be implemented by a cascade of block transforms.

According to teachings of the present invention, analysis and synthesis filter banks
are implemented by hybrid transforms that comprise a primary transform in cascade with
one or more secondary transforms. In one implementation, the primary transform is a
MDCT that is applied to source signal segments overlapping one another by one-half the
segment length and the secondary transform is a DCT that is applied to non-overlapping
blocks of MDCT coefficients for a particular frequency across time. The frequency
resolution of the filter banks may be increased by increasing the number of coefficients in
the blocks that are transformed by the one or more secondary transforms. The one or
more secondary transforms may be applied to blocks of MDCT coefficients having a
number of coefficients that varies with coefficient frequency, thereby allowing the
frequency resolution of the filter bank to be adapted in a wide variety of ways.
The various features of the present invention and its preferred embodiments may
be better understood by referring to the following discussion and the accompanying
drawings in which like reference numerals refer to like elements in the several figures.
The contents of the following discussion and the drawings are set forth as examples only
and should not be understood to represent limitations upon the scope of the present
invention.
f ACCOMPANYING
BRIEF DESCRIPTION OF/DRAWINGS
Fig. 1 is a schematic block diagram of a transmitter used in a coding system.
Fig. 2 is a schematic block diagram of a receiver used in a coding system.
Fig. 3 is a schematic block diagram of a device that may be used to implement
various aspects of the present invention.
Fig. 4 is a schematic block diagram of an analysis filter bank that incorporates
various aspects of the present invention.
Fig. 5 is a schematic block diagram of an analysis filter bank that incorporates
various aspects of the present invention.
MODES FOR CARRYING OUT THE INVENTION
A. Introduction
The present invention provides a filter bank that is implemented by a hybrid
transform whose frequency resolution can be easily adapted. Figs. 1 and 2 illustrate
schematic block diagrams of a transmitter and receiver, respectively, in an audio coding
system that may incorporate various aspects of the present invention. Features of the
illustrated transmitter and receiver are discussed briefly in the following sections.

Following this discussion, pertinent features of analysis and synthesis filter banks are
discussed.
1. Transmitter
The transmitter illustrated in Fig. 1 applies the analysis filter bank 3 to a source
signal received from the path 1 to generate spectral coefficients that represent the spectral
content of the source signal, applies the encoder 5 to the spectral coefficients to generate
encoded information, and applies the formatter 8 to the encoded information to generate
an output signal suitable for transmission along the path 9. The output signal may be
delivered immediately to a receiver or recorded for subsequent delivery. The analysis
filter bank 3 may be implemented in variety of ways as described below.
In this disclosure, terms like "encoder" and "encoding" are not intended to imply
any particular type of information processing. For example, encoding is often used to
reduce information capacity requirements; however, these terms in this disclosure do not
necessarily refer to this type of processing. The encoder 5 may perform essentially any
type of processing that is desired. In one implementation, encoded information is
generated by quantizing spectral coefficients according to a perceptual model using a
wide variety of quantization techniques including vector quantization and gain-adaptive
quantization described in U.S. patent 6,246,345 by Davidson et al., which issued June 12,
2001. No particular type of encoding is important to the present invention.
2. Receiver
The receiver illustrated in Fig. 2 applies the deformatter 23 to an input signal
received from the path 21 to obtain encoded information, applies the decoder 25 to the
encoded information to obtain spectral coefficients representing the spectral content of a
source signal, and applies the synthesis filter bank 27 to the spectral coefficients to
generate an output signal along the path 29 that is a replica of the source signal but may
not be an exact replica. The synthesis filter bank 27 may be implemented in a variety of
ways that are complementary to the implementation of the analysis filter bank 3.
In this disclosure, terms like "decoder" and "decoding" are not intended to imply
any particular type of information processing. The decoder 25 may perform essentially
any type of processing that is needed or desired. In one implementation that is inverse to
an encoding process described above, quantized spectral components are decoded into
dequantized spectral coefficients. No particular type of decoding is important to the
present invention.

B. Adaptive Hybrid Transform
The analysis filter bank 3 and the synthesis filter bank 27 comprise hybrid
transforms, which may be implemented as shown in Figs. 4 and 5, respectively.
The analysis filter bank 3 shown in Fig. 4 comprises a primary transform 43 and
one or more secondary transforms 45 in cascade with the primary transform. The primary
transform is applied to segments of a source signal to generate sets of spectral coefficients
that represent the spectral content of the source signal segments. Each of the one or more
secondary transforms is applied to blocks of spectral coefficients for a particular
frequency across time. The number of coefficients in each block is adapted in response to
a control signal.
The synthesis filter bank 27 shown in Fig. 5 comprises one or more inverse
secondary transforms 52 and an inverse primary transform 54 in cascade with the inverse
secondary transforms. Each of the one or more inverse secondary transforms generates
blocks of spectral coefficients for a particular frequency across time. The number of
coefficients in each block is adapted in response to a control signal. The blocks of spectral
coefficients are assembled into sets of spectral coefficients for a particular time across
frequency and the primary transform is applied to the sets of spectral coefficients to
generate segments of a signal that are combined to provide a replica of an original source
signal.
The primary transforms for the analysis filter bank and the synthesis filter bank
implement an analysis/synthesis system in which an inverse primary transform cancels
time-domain aliasing artifacts that are generated by the forward primary transform. For
example, the Modified Discrete Cosine Transform (MDCT) and the Inverse MDCT
(IMDCT) described in the Princen paper mentioned above implement the time-domain
equivalent of an oddly-stacked critically sampled single-sideband analysis/synthesis
system. These transforms are referred to herein as Oddly-Stacked Time-Domain Aliasing
Cancellation (O-TDAC) transforms. Another TDAC implementation is described in
Princen et al., "Analysis/Synthesis Filter Bank Design Based on Time Domain Aliasing
Cancellation," IEEE Trans, on Acoust.. Speech. Signal Proa, vol. ASSP-34, 1986, pp.
1153-1161. The analysis filter bank in this implementation comprises an application of a
MDCT and a Modified Discrete Sine Transform (MDST) to alternate signal segments. The
synthesis filter bank comprises an application of an IMDCT and an Inverse MDST
(TMDST). These transforms implement the time-domain equivalent of an evenly-stacked

critically sampled single-sideband analysis/synthesis system and are referred to as Evenly-
Stacked Time-Domain Aliasing Cancellation transforms.
The secondary transforms may be implemented by any of a number of transforms
including the Discrete Cosine Transform (DCT), the Discrete Sine Transform (DST), and
. the Discrete Fourier Transform (DFT).
In a preferred implementation of the analysis filter bank 3, a type-II DCT is used
in cascade with the O-TDAC MDCT mentioned above. In a counterpart implementation
of the synthesis filter bank 27, the O-TDAC IMDCT is used in cascade with a type-II
Inverse DCT (IDCT). These implementations are discussed in more detail below.
1. Analysis Filter Bank
Referring to Fig. 4, a sequence of source signal samples are received from the path
1 and stored in the buffer 41. The analyzer 47 is an optional component that determines
the number of source signal samples in each segment, or segment length, to use for
subsequent processing by applying some analytical process to the stored samples.
Essentially any analytical process may be used as desired. For example, amplitude
transients may be detected as described in the ATSC A/52A document cited above.
Information representing chosen segment lengths is passed along the path 2 to the
formatter 7 for inclusion in the output signal. Fixed length segments are used in an
alternative implementation that omits the analyzer 47 and the path 2.
a) Analysis Window Function
The window 42 forms a sequence of overlapping segments by weighting the
source signal samples in each segment with an analysis window function. The length and
shape of the analysis window function for each segment is adapted in response to the
segment length information received from the path 2. A wide variety of window functions
may be used but aKaiser-Bessel-Derived (KBD) window function is generally preferred
because it has excellent frequency selectivity properties. This window function is derived
from a Kaiser-Besset window function that may be expressed as:



An alpha value in the range from 4 to 7 works well for typical audio coding applications.
The derivation convolves the Kaiser-Bessel window function W{n) with a
rectangular window function having a length equal to the desired window function length N
minus an overlap interval v. See expression 2. This convolution may be simplified as shown
in expression 3.

The KBD analysis window function may be obtained by taking the square root of
the derived product-window WP(n). This analysis window function is shown in expression
The primary transform 43 transforms each segment of windowed source signal
samples into a set of spectral coefficients. Each coefficient in a set of coefficients
represents the spectral content of a windowed segment for a particular frequency. The


The primary transform may be implemented directly according to expression 5 or
it may be implemented by processes that are computationally more efficient such as those
using the Fast Fourier Transform (FFT) described in U.S. patent 5,394,473. The analysis
window function and the primary transform may be adapted in response to segment
length using essentially any process that may be desired. A few techniques are disclosed
in U.S. patent 5,214,742, U.S. patent 5,394,473, the ATSC A/52A document, and the
ISO/MPEG AAC document cited above.
Spectral coefficients representing the spectral content of the windowed source
signal segments for each of one or more respective frequencies are passed along
respective signal paths and stored in buffers. The transmitter shown in Fig. 4, for
example, passes spectral coefficients for each of two respective frequencies along one of
two signal paths for storage in the buffers 44a and 44b. Only two signal processing paths
are shown in Fig. 4 for illustrative clarity. Implementations of the analysis filter bank 3
for use in typical systems could have hundreds of paths.

Referring to the upper signal path shown in Fig. 4, spectral coefficients for a
particular frequency in a sequence of segments are stored in the buffer 44a and assembled
into blocks. The analyzer 48a determines the number of coefficients in each block, which
is the block length, and passes this length along the path 49a. This length may be
determined by analyzing the coefficients that are stored in the buffer 44a. No particular
method of analysis is critical in principle to the present invention. A few analytical
methods are described here.
One basic method forms the longest possible blocks of spectral coefficients in
which the coefficients in a respective block are sufficiently similar in magnitude. This
may be determined in a variety of ways. One way calculates differences in magnitude
between adjacent spectral coefficients and identifies the longest block of adjacent
coefficients in which the average difference is less than some threshold. Another way
uses spectral coefficients that are stored in buffers for multiple signal paths. This
approach sums the magnitude differences for a band of spectral coefficients and identifies
the longest block in which the average difference across the band is less than some
threshold. The width of the band may be commensurate with the so called critical
bandwidths of the human auditory system.
Another basic method relies on signal analysis that is performed by signal
encoding processes performed elsewhere in a transmitter. A transmitter that is compatible
with the bit stream standard described in the A/52A document cited above, for example,
generates an encoded signal with spectral coefficients represented as scaled values that
are associated with scale factors. The scale factors are analyzed to identify sequences of
MDCT coefficient sets that can share a common set of scale factors. The analyzer 48a
adapts the block length for its respective signal path to equal the number of coefficient
sets that share exponents.
d) Secondary Transform
The secondary transform 45a transforms each block of spectral coefficients into a
set of hybrid-transform coefficients. The length of the transform is adapted in response to
the block length information received from the path 49a. In a preferred implementation, a
type IIDCT is applied to blocks of spectral coefficients that do not overlap one another.
This transform may be expressed as:


The secondary transform may be implemented directly according to expression 7
or it may be implemented by known processes that are computationally more efficient
such as those described in chapter 4 of Rao et al., "Discrete Cosine Transform,"
Academic Press, Inc., 1990.
e) Formatter and Other Signal Paths
The formatter 46a is an optional component that may be used to assemble the
hybrid-transform coefficients and block length information into data that the encoder 5
and the formatter 7 can process. This allows the analysis filter bank 3 in the transmitter
shown in Fig. 1 to be implemented by a hybrid transform with minimal changes to the
rest of the transmitter.
The buffer 44b, the analyzer 48b, the secondary transform 45b, and the formatter
46b perform processes in the lower signal path that are analogous to those discussed
above for the respective components in the upper signal path.
J) Encoding
In typical systems, the encoder 5 generates encoded information that represents
the hybrid-transform coefficients in some encoded form. If perceptual encoding processes
are used, the hybrid-transform coefficients are encoded into a form that reduces
perceptual irrelevancy. Perceptual encoding processes usually cause spectral information
to be lost that cannot be recovered or recreated by the receiver. The possibility of this loss
is represented below by the symbol X(k,j), which denotes a possible modification to the
hybrid-transform coefficients generated by the hybrid transform. The use of such
encoding processes are not critical to the present invention.
2. Synthesis Filter Bank
Referring to Fig. 5, the deformatters 51a and 51b obtain hybrid transform
coefficients and block length information from data that is received from the paths 26a
and 26b, respectively. The block length information is passed along the paths 59a and

59b, and the hybrid-transform coefficients are passed to the inverse secondary transforms
52a and 52b. Only two signal processing paths are shown in Fig. 5 for illustrative clarity.
Implementations of the synthesis filter bank 27 for use in typical systems could have
hundreds of paths.
The deformatter 51b, the inverse secondary transform 52b, and the buffer 53b
perform processes in the lower signal path that are analogous to those discussed below for
the respective components in the upper signal path.
a) Deformatter
Referring to the upper signal path shown in Fig. 5, the deformatter 51a is an
optional component that may be used to disassemble sets of hybrid-transform coefficients
and block length information from data that is received from the deformatter 23 and the
decoder 25. This allows a hybrid-transform implementation of the synthesis filter bank 27
to be incorporated into an existing receiver as shown in Fig. 2 with minimal changes to
the rest of the receiver.
b) Inverse Secondary Transform
The inverse secondary transform 52a transforms a set of hybrid-transform
coefficients into a block of spectral coefficients that represent the spectral content for a
particular frequency of a sequence of source signal segments. The block of spectral
coefficients are stored in the buffer 53a. The length of the transform is adapted in
response to the block length information received from the path 59a. In a preferred
implementation, a type IIIDCT is applied to blocks of spectral coefficients that do not
overlap one another. This transform may be expressed as:

The inverse secondary transform may be implemented directly according to
expression 8 or it may be implemented by known processes that are computationally
more efficient.
c) Inverse Primary Transform
i The buffers 53a and 53b Store spectral coefficients and pass them to the inverse
primary transform 54 in such a way that the inverse primary transform receives sets of

spectral coefficients that represent the spectral content of respective source signal
segments. Segments of signal samples are generated by applying an inverse transform to
the sets of spectral coefficients and stored in the buffer 55. The length of the inverse
primary transform is adapted in response to segment length information received from the
; path 22. The O-TDAC TMDCT is used in a preferred implementation.
In typical applications, half of the MDCT coefficients are discarded in the
transmitter. The discarded coefficients may be recovered by the receiver using the
following expression:

where x = recovered signal sample.
The inverse primary transform may be implemented directly according to
expression 10 or it may be implemented by known processes that are computationally
more efficient such as those using the FFT described in U.S. patent 5,394,473.
(I) Synthesis Window Function
The window 56 generates an output signal along the path 29 by weighting the
segments of signal samples that are stored in the buffer 55 with a synthesis window
function and adding the weighted samples in overlapping segments to one another in the
overlapping portions. The inverse primary transform, synthesis window function and the
overlap-add process cancel at least a substantial portion of the time-domain aliasing
artifacts that were generated by the forward transform. Cancellation may not be exact
because of modifications to the transform coefficients that were caused by encoding
processes and by finite arithmetic precision in the calculations of the primary and
secondary transforms. The length and shape of the synthesis window function for each
segment is adapted in response to the segment length information received from the path
22. A KBD window function that is equal to the analysis window function WA show
above in expression 4 is used in a preferred implementation.

The synthesis window function and the inverse primary transform may be adapted
in response to the segment length information using processes such as those referred to
above.
C. Implementation
The preceding disclosure sets forth only a few implementations. A variety of
transforms and transform types may be used: Principles of the present invention may be
applied and implemented in a wide variety of ways.
Devices that incorporate various aspects of the present invention may be
implemented in a variety of ways including software for execution by a computer or some
other apparatus that includes more specialized components such as digital signal
processor (DSP) circuitry coupled to components similar to those found in a general-
purpose computer. Fig. 3 is a schematic block diagram of device 70 that may be used to
implement aspects of the present invention. DSP 72 provides computing resources. RAM 73
is system random access memory (RAM) used by DSP 72 for signal processing. ROM 74
represents some form of persistent storage such as read only memory (ROM) for storing
programs needed to operate device 70 and to carry out various aspects of the present
invention. I/O control 75 represents interface circuitry to receive and transmit signals by way
of communication channels 76,77. Analog-to-digital converters and digital-to-analog
converters may be included in I/O control 75 as desired to receive and/or transmit analog
signals. In the embodiment shown, all major system components connect to bus 71, which
may represent more than one physical bus; however, a bus architecture is not required to
implement the present invention.
In embodiments implemented in a general purpose computer system, additional
components may be included for interfacing to devices such as a keyboard or mouse and a
display, and for controlling a storage device having a storage medium such as magnetic tape
or disk, or an optical medium. The storage medium may be used to record programs of
instructions for operating systems, utilities and applications, and may include embodiments
of programs that implement various aspects of the present invention.
The functions required to practice various aspects of the present invention can be
performed by components that are implemented in a wide variety of ways including discrete
logic components, integrated circuits, one or more ASICs and/or program-controlled
processors. The manner in which these components are implemented is not important to
the present invention.

Software implementations of the present invention may be conveyed by a variety of
machine readable media such as baseband or modulated communication paths throughout
the spectrum including from supersonic to ultraviolet frequencies, or storage media that
convey information using essentially any recording technology including magnetic tape,
cards or disk, optical cards or disc, and detectable markings on media like paper.

WE CLAIM:
1. A method for generating an output signal that comprises:
receiving samples of a source signal having spectral content;
applying a primary transform (43) to overlapping segments of the samples to
generate a plurality of sets of spectral coefficients, wherein the primary transform (43)
is a Modified Discrete Cosine Transform and each set of spectral coefficients has
time-domain aliasing artifacts and represents the spectral content of a respective
source signal segment for a set of frequencies;
obtaining a plurality of spectral coefficients representing the same frequency in
the set of frequencies from the plurality of sets of spectral coefficients and assembling
the plurality of spectral coefficients into one or more blocks of spectral coefficients,
wherein the number of spectral coefficients that are assembled in each of the one or
more blocks is adapted in response to a block-length control signal;
applying a secondary transform (45 a, 45b) to the one or more blocks of
spectral coefficients to generate one or more sets of hybrid-transform coefficients,
wherein the secondary transform (45a, 45b) is a Discrete Cosine Transform that is
applied to blocks of spectral coefficients that do not overlap one another and the
length of the secondary transform (45a, 45b) that is applied to each of the one or more
blocks of spectral coefficients is adapted in response to the block-length control
signal; and
assembling information representing the one or more sets of hybrid-transform
coefficients and the block-length control signal into the output signal.
2. The method as claimed in claim 1, which involves:
generating a measure of similarity for spectral component magnitudes within a
plurality of sets of spectral components; and
generating the block-length control signal in response to the measure of
similarity.
3. The method as claimed in claim 1 or 2, which involves:
analyzing samples of the source signal to generate a segment-length control
signal; and

applying an analysis window function (42) to a segment of samples of the
source signal, wherein shape or length of the analysis window function (42) is adapted
in response to the segment-length control signal.
4. The method as claimed in claim 1 or 3, wherein the primary transform (43) has a set of
basis functions and the method comprises adapting the set of basis functions in response to the
segment-length control signal.
5. A method for generating an output signal that comprises:
receiving an input signal that represents spectral content of a source signal;
obtaining one or more sets of hybrid-transform coefficients and a block-length
control signal from the input signal;
applying an inverse secondary transform (52a, 52b) to the one or more sets of
hybrid-transform coefficients to generate one or more blocks of spectral coefficients
representing spectral content of the source signal for the same frequency in a set of
frequencies, wherein the inverse secondary transform (52a, 52b) is an Inverse Discrete
Cosine Transform that is applied to sets of hytbrid-transform coefficients representing
blocks of spectral coefficients that do not overlap one another and the length of the
inverse secondary transform (52a, 52b) that is applied to the sets of hybrid-transform
coefficients is adapted in response to the block-length control signal;
assembling the spectral coefficients into sets of spectral coefficients, wherein
each set of spectral coefficients has time-domain aliasing artifacts and represents the
spectral content of a segment of the source signal for all frequencies in the set of
frequencies;
applying an inverse primary transform (54) to the sets of spectral coefficients
to generate output signal segments that correspond to segments of the source signal,
wherein the inverse primary transform (54) is an Inverse Modified Discrete Cosine
Transform and the inverse primary transform (54) substantially cancels the time-
domain aliasing artifacts.
6. The method as claimed in claim 5, which involves:
obtaining a segment-length control signal from the input signal; and
applying a synthesis window function (56) to an output signal segment,
wherein shape or length of the synthesis window function (56) is adapted in response
to the segment-length control signal.

7. The method as claimed in claim 5 or 6, wherein the inverse primary transform (54) has
a set of basis functions and the method comprises adapting the set of basis functions in
response to the segment-length control signal.
- 8. An apparatus for generating an output signal that comprises:
(a) an input terminal (1);
(b) an output terminal (4a, 4b); and
(c) signal processing circuitry coupled to the input terminal (1) and the output terminal
(4a, 4b), wherein the signal processing circuitry is adapted to:
receive samples of a source signal having spectral content from the
input terminal;
apply a primary transform (43) to overlapping segments of the samples
to generate a plurality of sets of spectral coefficients, wherein the primary
transform (43) is a Modified Discrete Cosine Transform and each set of
spectral coefficients has time-domain aliasing artifacts and represents the
spectral content of a respective source signal segment for a set of frequencies;
obtain a plurality of spectral coefficients representing the same
frequency in the set of frequencies from the plurality of sets of spectral
coefficients and assemble the plurality of spectral coefficients into one or more
blocks of spectral coefficients, wherein the number of spectral coefficients that
are assembled in each of the one or more blocks is adapted in response to a
block-length control signal;
apply a secondary transform (45a, 45b) to the one or more blocks of
spectral coefficients to generate one or more sets of hybrid-transform
coefficients, wherein the secondary transform (45a, 45b) is a Discrete Cosine
Transform that is applied to blocks of spectral coefficients that do not overlap
one another and the length of the secondary transform (45 a, 45b) that is
applied to each of the one or more blocks of spectral coefficients is adapted in
response to the block-length control signal; and
assemble information representing the one or more sets of hybrid-
transform coefficients and the block-length control signal into the output signal
that is sent to the output terminal (4a, 4b).

9. The apparatus as claimed in claim 8, wherein the signal processing circuitry is adapted
to:
generate a measure of similarity for spectral component magnitudes within a
plurality of sets of spectral components; and
generate the block-length control signal in response to the measure of
similarity.
10. The apparatus as claimed in claim 8 or 9, wherein the signal processing circuitry is
adapted to:
analyze samples of the source signal to generate a segment-length control
signal; and
apply an analysis window function (42) to a segment of samples of the source
signal, wherein shape or length of the analysis window function (42) is adapted in
response to the segment-length control signal.
11. The apparatus as claimed in claim 8 or 10, wherein the primary transform (43) has a
set of basis functions and the signal processing circuitry adapts the set of basis functions in
response to the segment-length control signal.
12. An apparatus for generating an output signal that comprises:

(a) an input terminal (26a, 26b);
(b) an output terminal (29); and
(c) signal processing circuitry coupled to the input terminal (26a, 26b) and the output
terminal (29), wherein the signal processing circuitry is adapted to:
receive an input signal that represents spectral content of a source signal from
the intput terminal;
obtain one or more sets of hybrid-transform coefficients and a block-length
control signal from the input signal;
apply an inverse secondary transform (52a, 52b) to the one or more sets of
hybrid-transform coefficients to generate one or more blocks of spectral coefficients
representing spectral content of the source signal for the same frequency in a set of
frequencies, wherein the inverse secondary transform (52a, 52b) is an Inverse Discrete
Cosine Transform that is applied to sets of hytbrid-transform coefficients representing
blocks of spectral coefficients that do not overlap one another and the length of the

inverse secondary transform (52a, 52b) that is applied to the sets of hybrid-transform
coefficients is adapted in response to the block-length control signal;
assemble the spectral coefficients into sets of spectral coefficients, wherein
each set of spectral coefficients has time-domain aliasing artifacts and represents the
spectral content of a segment of the source signal for all frequencies in the set of
frequencies; and
apply an inverse primary transform (54) to the sets of spectral coefficients to
generate output signal segments that correspond to segments of the source signal,
wherein the inverse primary transform (54) is an Inverse Modified Discrete Cosine
Transform and the inverse primary transform (54) substantially cancels the time-
domain aliasing artifacts and the output signal segments are sent to the output terminal
(29).
13. The apparatus as claimed in claim 12, wherein the signal processing circuitry is
adapted to:
obtain a segment-length control signal from the input signal; and
apply a synthesis window function (56) to an output signal segment, wherein
shape or length of the synthesis window function (56) is adapted in response to the
segment-length control signal.
14. The apparatus as claimed in claim 12 or 13, wherein the inverse primary transform
(54) has a set of basis functions and the signal processing circuitry adapts the set of basis
functions in response to the segment-length control signal.



ABSTRACT OF THE DISCLOSURE


METHOD AND APPARATUS FOR GENERATING AN OUTPUT SIGNAL
Analysis and synthesis filter banks (3) such as those used in audio and video coding
systems are each implemented by a hybrid transform that comprises a primary transform (43) in
cascade with one or more secondary transforms (45a, 45b). The primary transforms for the filter
banks implement an analysis/synthesis system in which time-domain aliasing artifacts are
cancelled. The secondary transforms (45a, 45b), which are in cascade with the primary
transforms (43), are applied to blocks of transform coefficients. The length of the blocks is
varied to adapt the time resolution of the analysis and synthesis filter banks.

Documents:

02084-kolnp-2006 abstract.pdf

02084-kolnp-2006 assignment.pdf

02084-kolnp-2006 claims.pdf

02084-kolnp-2006 correspondenceothers.pdf

02084-kolnp-2006 deascription(complete).pdf

02084-kolnp-2006 drawings.pdf

02084-kolnp-2006 form1.pdf

02084-kolnp-2006 form3.pdf

02084-kolnp-2006 form5.pdf

02084-kolnp-2006 international publication.pdf

02084-kolnp-2006 international searchauthority report.pdf

02084-kolnp-2006 others.pdf

02084-kolnp-2006 prioritydocument.pdf

2084-KOLNP-2006-(07-12-2011)-CORRESPONDENCE.pdf

2084-KOLNP-2006-(09-01-2012)-CORRESPONDENCE.pdf

2084-KOLNP-2006-ABSTRACT-1.1.pdf

2084-KOLNP-2006-AMANDED CLAIMS.pdf

2084-KOLNP-2006-ASSIGNMENT.pdf

2084-KOLNP-2006-CANCELLED PAGES.pdf

2084-KOLNP-2006-CORRESPONDENCE.pdf

2084-KOLNP-2006-DESCRIPTION (COMPLETE)-1.1.pdf

2084-KOLNP-2006-DRAWINGS-1.1.pdf

2084-KOLNP-2006-EXAMINATION REPORT REPLY RECIEVED.pdf

2084-KOLNP-2006-EXAMINATION REPORT.pdf

2084-KOLNP-2006-FORM 1-1.1.pdf

2084-KOLNP-2006-FORM 13 1.1.pdf

2084-KOLNP-2006-FORM 13.pdf

2084-KOLNP-2006-FORM 18 1.1.pdf

2084-kolnp-2006-form 18.pdf

2084-KOLNP-2006-FORM 2.pdf

2084-KOLNP-2006-GPA.pdf

2084-KOLNP-2006-GRANTED-ABSTRACT.pdf

2084-KOLNP-2006-GRANTED-CLAIMS.pdf

2084-KOLNP-2006-GRANTED-DESCRIPTION (COMPLETE).pdf

2084-KOLNP-2006-GRANTED-DRAWINGS.pdf

2084-KOLNP-2006-GRANTED-FORM 1.pdf

2084-KOLNP-2006-GRANTED-FORM 2.pdf

2084-KOLNP-2006-GRANTED-FORM 3.pdf

2084-KOLNP-2006-GRANTED-FORM 5.pdf

2084-KOLNP-2006-GRANTED-SPECIFICATION-COMPLETE.pdf

2084-KOLNP-2006-INTERNATIONAL SEARCH REPORT & OTHERS.pdf

2084-KOLNP-2006-OTHERS-1.1.pdf

2084-KOLNP-2006-OTHERS.pdf

2084-KOLNP-2006-PA.pdf

2084-KOLNP-2006-PETITION UNDER RULE 137 1.1.pdf

2084-KOLNP-2006-PETITION UNDER RULE 137.pdf

2084-KOLNP-2006-REPLY TO EXAMINATION REPORT 1.1.pdf

abstract-02084-kolnp-2006.jpg


Patent Number 255723
Indian Patent Application Number 2084/KOLNP/2006
PG Journal Number 12/2013
Publication Date 22-Mar-2013
Grant Date 19-Mar-2013
Date of Filing 24-Jul-2006
Name of Patentee DOLBY LABORATORIES LICENSING CORPORATION
Applicant Address 100, POTRERO AVENUE, SAN FRANCISCO, CA 94103-4813, UNITED STATES OF AEMRICA
Inventors:
# Inventor's Name Inventor's Address
1 VINTON, MARK STUART C/O. DOLBY LABORATORIES LICENSING CORPORATION, 100, POTRERO AVENUE, SAN FRANCISCO, CA 94103 UNITED STATES OF AEMRICA
2 DAVIDSON, GRANT, ALLEN C/O. DOLBY LABORATORIES LICENSING CORPORATION, 100, POTRERO AVENUE, SAN FRANCISCO, CA 94103 UNITED STATES OF AEMRICA
PCT International Classification Number G06T9/00
PCT International Application Number PCT/US2005/001923
PCT International Filing date 2005-01-21
PCT Conventions:
# PCT Application Number Date of Convention Priority Country
1 10/783,951 2004-02-19 U.S.A.