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BACKGROUND OF THE INVENTION
The present invention relates generally to vocoders and methods of
operating vocoders. For purposes of the present invention, vocoders
receive digitized samples of an analog voice signal and compress or encode
the samples so that a resulting code characterizes the analog voice
signal. The resulting code may then be applied to a channel, such as a
transmission channel or a storage device. Such channels typically have a
bandwidth which accommodates the resulting code, but is too low to
accommodate the digitized samples. The resulting code, characterizes the
original analog voice signal so that it may be decoded or expanded by a
vocoder to produce samples that reproduce the voice signal as perceptually
accurately as possible. The present invention relates to vocoders which
seek to achieve optimal voice quality in the reproduced voice signal for a
given bit rate. Specifically, the present invention relates to vocoders
which utilize a variable frame rate in the compression or encoding
operations.
Voice represents a complicated analog signal which is not easily compressed
so that an accurate reproduction will result. For example, vowel sounds
require a relatively long analysis window so that a relatively high degree
of spectral accuracy can be achieved. The relatively high degree of
spectral accuracy is required so that a later synthesized vowel sound will
appear to accurately reproduce the original analog voice signal to a
listener. On the other hand, consonant sounds require a relatively short
analysis window so that a relatively high degree of temporal resolution
may be achieved. The high degree of temporal resolution is required so
that a later synthesized consonant sound will appear as an accurate
reproduction of the original voice signal to a listener.
FIG. 1 shows the relationship between spectral accuracy and temporal
resolution. Generally speaking, at a given bit rate a vocoder can achieve
a high spectral accuracy by sacrificing temporal resolution, or can
achieve a high degree of temporal resolution by sacrificing spectral
accuracy.
Many conventional vocoders which apply coded voice to a fixed rate channel
do not vary frame rate. Accordingly, designs of such systems attempt to
trade off temporal resolution, which is needed to achieve accurate
reproduction of consonants, with spectral accurate, which is needed to
achieve accurate reproduction of vowels, and vice versa. Consequently,
noticeably inaccurate reproductions for both vowels and consonants
results. Reproduced consonants become slightly slurred and vowels do not
faithfully reproduce nasal perceptions and voiced fricative perceptions.
A conventional solution to the problem of noticeably inaccurate
reproductions of vowel and consonant sounds varies the analysis window, or
frame, over which samples are coded so that short frames are used for
analysis of consonants and long frames are used for analysis of vowels.
However, a cumbersome vocoder architecture results from conventional
implementations which adapt such variable frame rate vocoding methods for
use with fixed rate channels. Such conventional implementations typically
require elaborate buffering schemes with feedback systems to maintain a
constant bit rate in spite of the variable frame rate. In some
conventional systems, the buffering introduces an unacceptable delay.
SUMMARY OF THE INVENTION
Accordingly, it is an object of the present invention to provide an
improved vocoding method which may be implemented using a wide variety of
vocoder architectures and which permits variable frame rates at constant
bit rates without the use of significant buffering or feedback schemes.
Another object of the present invention concerns providing an improved
vocoding method that utilizes a base frame that occurs at a constant rate
but contains a variable number of subframes depending upon whether a voice
signal being analyzed resembles a vowel sound or a consonant sound.
The above and other objects and advantages of the present invention are
carried out in one form by a method of operating a vocoder to compress
voice data samples. The method first selects a particular one of a
plurality of possible subframe rates. Subsequently, an analyzing step
operates on at least a portion of the voice data samples to produce a
predictive code which represents the analyzed samples. Additionally, a
quantizing step transforms the predictive code into a quantized code
wherein the bit length of the quantized code is defined by the selected
subframe rate and a bit rate parameter of a fixed rate channel into which
the quantized code is applied.
BRIEF DESCRIPTION OF THE DRAWINGS
A more complete understanding of the present invention may be derived by
reference to the detailed description and claims when considered in
connection with the accompanying drawings, wherein like reference numbers
indicate like features throughout the drawings, and wherein;
FIG. 1 shows a rate distortion boundary curve;
FIG. 2 shows a vocoder architecture utilized in implementing the present
invention;
FIG. 3 shows a flow diagram of the present invention; and
FIGS. 4A through 4F show exemplary definitions of various fields within a
base frame of data output by the vocoder of FIG. 2.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT
FIG. 1 shows a rate-distortion boundary curve for applying encoded voice
signals to a fixed rate channel. It represents a monotonic, decreasing,
convex curve. The present invention causes a vocoder (discussed below) to
operate at a plurality of points on this rate-distortion boundary rather
than at only one point. However, during any one base frame, the present
invention operates at only one point. Accordingly, the present invention
selects only one of a plurality of points on this rate-distortion boundary
at which to operate. This selection occurs once during each base frame.
A point 10 shown in FIG. 1 represents a situation where a voice signal may
be described with relatively high spectral accuracy, but relatively low
temporal resolution. This situation is appropriate for encoding vowel
sounds. On the other hand, a point 12 causes a code generated by the
present invention to exhibit a high temporal resolution, but only a
relatively low spectral accuracy. Such a point of operation is appropriate
for describing certain consonant sounds. Additionally, a point 14 which
resides between points 10 and 12 on the rate-distortion boundary,
describes the sound using a moderate degree of temporal resolution and a
moderate degree of spectral accuracy.
FIG. 2 shows a structure which the present invention utilizes in performing
the methods described herein. FIG. 2 shows an analysis vocoder 16a and a
synthesis vocoder 16b. As shown in FIG. 2, each of vocoders 16 may be
identical in structure. In fact, vocoder 16b may represent vocoder 16a at
a later point in time if a fixed rate channel 18 through which an encoded
signal is sent represents a memory channel. Conversely, vocoder 16b may
represent a different vocoder from vocoder 16a which, having knowledge of
the coding scheme utilized by vocoder 16a, may decode and synthesize a
signal received from fixed rate channel 18.
Vocoders 16a and 16b each represent computerized signal processing devices.
Thus, vocoder 16a has a processor 20a. Processor 20a couples to a computer
bus 22a which in turn couples to a digital signal processor 24a, a memory
26a and an input/output (I/O) circuit 28a. I/O circuit 28a has a first I/O
port which connects to a terminal 30a. This first I/O port transfers
analog signals into and out from vocoder 16a. I/O circuit 28a additionally
has a second port which couples to fixed rate channel 18. This second port
transfers digitally encoded voice signals into and out from vocoder 16a.
Vocoder 16b has a processor 20b which couples to a computer bus 22b.
Computer bus 22b couples to a digital signal processor 24b, a memory 26b
and an I/O circuit 28b. I/O circuit 28b has a first port which couples to
a terminal 30b. This first I/O port transfers analog signals into and out
from vocoder 16b. Additionally, I/O circuit 18b has a second port which
couples to fixed rate channel 18. This second port transfers digitally
encoded data into and out from vocoder 16b.
Fixed rate channel 18 may represent a memory or storage device for which
compression of voice data samples is needed because a quantity of voice
data samples occurring within a given period of time would be too great
for such memory device or storage. Alternatively, fixed rate channel 18
may represent a transmission channel, such as a telephone line, an RF
transmission channel, or the like, which accepts data at a constant rate.
The application of data to a telephone line represents one common use of a
fixed rate channel.
In operation, analysis vocoder 16a inputs voice data from terminal 30a and
digitizes such voice data in I/O circuit 28a. Such digitized samples are
generally manipulated and compressed to a point where they may be applied
to fixed rate channel 18. Such manipulation and compression occurs
primarily through the operation of processor 20a acting upon the digitized
samples with the use of digital signal processor 24a and memory 26a.
Synthesizer vocoder 16b performs an inverse operation. Compressed data
samples are applied to I/O circuit 28b from fixed rate channel 18.
Processor 20b, utilizing digital signal processor 24b and memory 26b,
decompresses and expands this compressed data to a point where I/O circuit
28b outputs a multiplicity of voice data samples at terminal 30b. After
some analog signal conditioning, the voice data samples output from
synthesizer vocoder 16b represent a reproduction of the input voice data.
In the preferred embodiment, analysis vocoder 16a takes 180 samples of
analog voice data every 22.5 milliseconds (ms), and outputs data to fixed
rate channel 18 at a constant base frame rate of 54 bits every 22.5
milliseconds, or a 2400 bits per second constant rate. Those skilled in
the art will recognize that the vocoder architecture described in FIG. 2
and other similar architectures represent general purpose vocoders which
are extremely flexible and may be operated to perform many different
methods. Furthermore, the methods performed by such vocoders are
established to a large degree by the programming which controls processors
20.
FIG. 3 describes the operation of vocoders 16 in compressing and expanding
voice data. FIG. 3 is divided into an analysis process 31 which is
performed prior to application of data to fixed rate channel 18 by vocoder
16a. (see FIG. 2) and a synthesis process 51 which is applied to data
obtained from fixed rate channel 18 and is practiced by vocoder 16b.
Analysis process 31 starts with the receipt of a multiplicity of voice
data samples. In the preferred embodiment, analysis process 31 receives
180 voice data samples every 22.5 milliseconds, as shown in beginning
state 32.
The present invention compresses the voice data samples into a base frame
of data that exhibits a constant base frame rate. Furthermore, the base
frame includes one or more subframes. The base frame will include only one
subframe when process 31 analyzes a vowel sound. This situation describes
point 10, shown in FIG. 1. In this situation, the vowel sound will be
described with a high degree of spectral accuracy, but a low degree of
temporal resolution.
Several subframes, a maximum three or four in the preferred embodiment, are
utilized to describe consonant sounds. For a consonant sound, the sounds
described by each of the subframes within a single base frame exhibit
relatively low spectral accuracy. However, due to the quantity of
subframes a relatively high temporal resolution results. Thus, such
subframes may be characterized as being operations at point 12 in FIG. 1.
From beginning state 32, a spectral change measurement task 34 is
performed. Vowel sounds tend to exhibit a relatively constant spectrum
over the duration of a base frame. Consonants tend to exhibit a relatively
variable spectrum over the duration of a base frame. Accordingly, vowel
sounds may be distinguished from consonant sounds by measuring spectral
changes. Thus, spectral change measurement process 34 performs a linear
predictive coding (LPC) analysis to obtain coefficients useful in making a
measurement of spectral change.
However, in order to save computer processing time, the preferred
embodiment does not perform a complete LPC analysis to measure spectral
change. Since the present invention contemplates only a relatively small
number of possible subframe rate choices, only a few spectrum coefficients
which tend to influence the spectrum representation most significantly are
generated. The preferred embodiment generates only four spectrum
coefficients in spectral change measurement process 34. Those skilled in
the art will recognize that such coefficients may represent predictor
coefficients, or may represent predictor coefficients transformed into
reflector coefficients or other coefficient representations such as log
area ratios or uniform spectral sensitivities.
Furthermore, spectral change measurement process 34 obtains sets of these
few LPC spectrum coefficients for each subframe occurring within a base
frame at the maximum subframe rate. For example, if the maximum subframe
rate is four subframes per base frame, and the base frame contemplates 180
voice data samples every 22.5 ms, then a first set of spectrum
coefficients is obtained for the first 45 of the 180 samples, or the first
5.625 ms of the 22.5 ms base frame. A second set of spectrum coefficients
is obtained for the second 45 of the 180 samples, or for the period
occurring between 5.625 and 11.25 ms after the start of the base frame.
Likewise, a third set of spectrum coefficients is obtained for the third
45 of the 180 samples. This corresponds to the period of time occurring
between 11.25 and 16.875 ms after the start of the base frame. Finally, a
fourth set of spectrum coefficients is obtained for the fourth 45 of the
180 samples, or for the time period between 16.875 and 22.5 ms after the
start of the base frame. If each set of spectrum coefficients consists of
4 coefficients, then a total of 16 coefficients are obtained.
Measurement process 34 next detects the amount of change occurring between
each element of the obtained set of coefficients and corresponding
elements of a set of coefficients obtained from the immediately previous
subframe. Such detection of change may occur through the use of
subtraction operations between corresponding elements of successive
subframes. These change values are then combined into a single number that
may be compared against predetermined thresholds to indicate appropriate
subframe rates. Such combining may be accomplished by adding coefficient
changes together.
As an example, a resulting combined spectral change number which is greater
than a greatest predetermined threshold would suggest that a consonant
sound is described by the voice data samples contained in the base frame
and that a maximum subframe rate should be utilized throughout the current
base frame. Alternatively, if the combined number is less than a least
predetermined threshold, then a sound resembling a vowel sound is
described by the voice data samples in the base frame, and a minimum
subframe rate is appropriate. The minimum subframe rate would typically be
one subframe per base frame. If the combined number exhibited a value
between the greatest and the least predetermined thresholds, then a medium
subframe rate, such as two subframes per base frame, would be appropriate.
Alternatively, the spectral change between each subframe may be compared
with the threshold, and the number of changes greater than the threshold
used as an indication of location on the rate distortion board.
The number of subframes per frame represents the subframe rate and is the
output from spectral change measurement process 34. This output increases
in value in response to an increase in spectral change. The output from
spectral change measurement process 34 is used by several other processes
within analysis process 31.
An LPC analysis process utilizes the output from spectral change
measurement process 34 in performing a conventional LPC analysis of the
voice data samples obtained from state 32. This subframe rate information
tells LPC analysis process 36 the number or portion of samples from the
base frame to analyze and the number of times such analyses are required
for the base frame of 180 data voice samples and the approximate temporal
boundary between similar regions. If spectral change measurement process
34 outputs a value of only one subframe per base frame, then only one
analysis is required and this analysis utilizes all 180 of the voice data
samples. However, if spectral change measurement process 34 outputs a
value of 4 subframes per base frame, then 4 separate independent analyses
are needed. The first of the 4 LPC analyses utilizes the first 45 of the
180 samples, the second analysis utilizes the second 45 of the 180 voice
data samples, the third analysis utilizes the third 45 of the 180 voice
data samples and the fourth utilizes the fourth 45 of the 180 voice data
samples.
The output from LPC analysis process 36 is a predictive code which includes
a set of numbers describing excitation, energy, and spectrum for each
analysis performed on the base frame of voice data samples. Those skilled
in the art will recognize that a conventional LPC analysis may compress
voice data samples into a smaller amount of data than are used to describe
the voice data samples. However, additional compression may occur before
such information is applied to fixed rate channel 18.
Thus, an excitation quantization process 38 inputs the excitation output
from LPC analysis process 36. Excitation quantization process 38 provides
additional compression of the excitation information. The present
invention contemplates the application of conventional quantization
techniques to excitation information 38. Such techniques may introduce a
wide variation in the amount of compression achieved. For lower rate
channels, excitation information may advantageously be quantized as a
single pitch value. Additionally, a predetermined unique code may be
established to indicate whether the excitation is voiced or unvoiced. For
higher channel rates, the excitation may describe a complex waveform
having many different frequency components and phase relationships. The
precise quantization process utilized depends upon the number of available
bits in an excitation field of a frame of data applied to channel 18
(discussed below). In general, a greater number of bits available within
the excitation portion of the frame causes in a more accurate reproduction
of an analog voice signal by synthesis process 51. The preferred
embodiment of the present invention contemplates utilizing only one
excitation for an entire base frame regardless of the number of subframes
contained therein. Thus, this excitation information is assumed to remain
relatively constant throughout the base frame.
Similarly, an energy quantization process 40 receives energy information
from LPC analysis process 36 for quantization. Those skilled in the art
will recognize that the energy may also be called gain or amplitude. The
present invention contemplates a conventional energy quantization process.
In the preferred embodiment of the present invention, a unique energy
value is obtained for each subframe within the base frame. Thus, energy
quantization process 40 generates a quantity of energy values which
depends upon the number of subframes contained within the base frame. The
quantity of bits used to described energy values depends upon the size of
fields allocated for energy information in a frame of data which is to be
applied to channel 18.
A spectrum quantization process 42 utilized by the present invention
contemplates the use of vector quantization (VQ) of spectrum information
into a quantized code. VQ represents a method of compressing data which
takes advantage of linear and non-linear redundancies. An "off-line"
process (not shown) that occurs during the design of vocoder 16 (see FIG.
2) populates various codebooks. This populating process derives a set of
spectrum coefficients, which may be referred to as reference patterns,
code vectors, or templates. The entire set of references patterns within a
codebook represents all possible speech spectral sounds. The set is then
arranged in a memory device, such as memory 26 (see FIG. 2), to form a
codebook, or library, so that an efficient search may be performed in real
time to detect which one of all the reference patterns contained in the
codebook represents a nearest matching pattern to a particular set of
spectrum coefficients which may be produced by the LPC analysis process
36. A pointer, or reference pattern descriptor code, that uniquely
identifies the nearest matching reference pattern is then selected as the
quantized value and serves as the output from spectrum quantization
process 42. Thus, the spectrum coefficients are transformed into reference
pattern descriptor codes.
The use of a greater quantity of reference patterns in a codebook permits
closer matches between analyzed spectrum coefficients from LPC analysis
process 36 and the reference patterns contained within the codebook.
Closer matches are desirable because they permit a more accurate spectral
representation of the spectral coefficients in the output from spectrum
quantization process 42. However, a greater number of reference patterns
in a given codebook requires a greater number of bits for description of
reference pattern descriptor codes that uniquely define nearest matching
reference patterns.
An N bit reference pattern descriptor code can uniquely identify a
reference pattern obtained from a codebook having less than 2.sup.N
reference patterns. For example, if a codebook contains 256 reference
patterns, then all possible sounds are characterized as being a set of
only 256 sounds. A listener can detect many more than 256 sounds. Thus,
much spectral inaccuracy is introduced by using a codebook having only 256
reference patterns. However, the reference pattern descriptor code for
such a codebook requires no more than 8-bits to uniquely describe any one
of the 256 reference patterns.
On the other hand, if a codebook contains 65,536 reference patterns, then a
greater likelihood exists that a given set of spectrum coefficients from
LPC analysis process 36 will find a very close match within the reference
patterns. As a result, spectral accuracy is greatly improved over the use
of a codebook containing only 256 samples. On the other hand, a
corresponding reference pattern descriptor code for a codebook containing
approximately 65,000 samples requires at least 16 bits for a unique
identification of any one of the 65,536 reference patterns.
In the present invention, a switching step 44 chooses only one of a
plurality of quantization tasks 46 to operate upon spectrum coefficients
generated by LPC analysis process 36. The choice performed by switching
step 46 occurs in response to the output from spectral change measurement
process 34. A VQ task 46a is selected when the output from spectral change
measurement process 34 indicates a maximum rate for subframes within the
base frame. VQ task 46a makes a smallest codebook formed in memory 26 (see
FIG. 1) available for the VQ operation performed thereby. Consequently, a
resulting reference pattern descriptor code output from VQ task 46a may
not demonstrate a high degree of spectral accuracy, but contains only a
few bits. For example, the codebook utilized by VQ task 46a may contain
only 256 reference patterns and VQ task 46a may output an 8-bit reference
pattern descriptor code. As discussed above, when the maximum subframe
rate is output from spectral change measurement process 34, the base frame
of 180 voice data samples is partitioned into subframes and LPC analyses
are performed on each of the subframes independently of the other
subframes. Likewise, VQ task 46a performs a vector quantization operation
for each of the subframes defined by the indicated subframe rate.
Consequently, VQ task 46a outputs separate reference pattern descriptor
codes for each of the subframes occurring within a base frame at the
maximum subfame rate. Each of the reference pattern descriptor codes
describes the spectrum for only one of the subframes.
When switching step 44 selects task 46c, and task 46c represents a vector
quantization task, a largest codebook contained within memory 26 (see FIG.
2) is made available for a VQ search. A resulting reference pattern
descriptor code output from VQ task 46c demonstrates a high degree of
spectral accuracy, but also requires a large number of bits. For example,
if the codebook utilized by VQ task 46c contains 65,536 reference
patterns, then a resulting reference pattern descriptor code would contain
at least 16 bits.
When switching step 44 selects VQ task 46b, a medium size codebook formed
in memory 26 is used for the VQ operation. Spectral accuracy and bit
requirements fall between those outlined above for VQ task 46a and 46c.
For example, a codebook containing 4,096 reference patterns may be used,
and a resulting reference pattern descriptor code might contain 12 bits.
A task 50 formats or establishes a base frame of data from quantized code
output from excitation quantization process 38, energy quantization
process 40, and spectrum quantization process 42 for application to fixed
rate channel 18. FIGS. 4A-4E show examples of possible predetermined
formats that task 50 might utilize in forming the base frame of data. Each
of FIGS. 4A-4E describe a base frame containing 54 bits which, in the
preferred embodiment, would be applied to channel 18 over 22.5
milliseconds to achieve a 2400 bits per second constant bit rate.
FIG. 4A shows an example of a format for a base frame of data in a single
subframe per base frame situation. In this base frame of data, one bit is
allocated for a sink bit, and two bits are allocated to describe the
subframe rate. The subframe rate bits apply to all subframes in the base
frame, which is only one subframe in this example, but permit the use of
up to 4 different subframe rates. In the FIG. 4A example, 27 bits of the
base frame are allocated to describing the excitation information output
from excitation quantization process 38, eight bits are allocated to
describing the energy information obtained from energy quantization
process 40, and 16 bits are allocated to describing the spectrum
information obtained from spectrum quantization process 42.
FIG. 4B shows base frame of data which contains two subframes. In FIG. 4B,
one bit has been allocated for synchronization and two bits have been
allocated for defining subframe rate as described above in connection with
FIG. 4A. Seventeen bits are allocated to describing the excitation. This
single excitation information field is utilized in connection with each of
the two subframes within the base frame of data. Each of the two subframes
allocate 5 bits to describing energy for that particular subframe and 12
bits for describing the spectrum for that particular subframe.
FIG. 4C shows an example of a base frame of data that contains three
subframes. The FIG. 4C base frame allocates 1 bit for synchronization and
2 bits for subframe rate definition as described above in connection with
FIG. 4A. Additionally, the FIG. 4C base frame allocates 12 bits for
excitation, and the 12 excitation bits apply to all three subframes in
this base frame. Each of the 3 subframes allocates 5 bits for an energy
information field and 8 bits for a spectrum information field.
FIG. 4D shows a base frame of data that contains four subframes. FIG. 4D
allocates 1 bit to synchronization and 2 bits to subframe rate, as
discussed above in connection with FIG. 4A. FIG. 4D allocates 7 bits to
excitation. The excitation field applies to each of the four subframes
contained within this base frame of data. Additionally, a 4-bit field is
allocated as a base energy field. The base energy field also applies to
each of the four subframes within this base frame of data. Each of the
four subframes contains a 2-bit energy difference field and an 8-bit
spectrum field. The 2-bit energy difference field is intended to describe
a change in energy from the base energy value contained in the base energy
field. Alternatively, energy difference fields may describe the change in
energy from the energy description of a previous subframe within the base
frame of data.
FIG. 4E represents an alternative embodiment to the format shown in FIG.
4A. As discussed above, FIG. 4A allocates only 16 bits to a spectrum
field. Using VQ, this 16-bit spectrum field suggests that a 16-bit
reference pattern descriptor code and a codebook having less than 2.sup.16
reference patterns are to be employed. The conventional LPC analysis
process may generate 10 spectrum coefficients for each subframe. If a
codebook contains 65,536 reference patterns and each reference pattern
contains ten values, an undesirably large amount of memory may be required
for the codebook. Furthermore, an undesirably large processing capability
may be required in order to search through such a codebook for a nearest
matching pattern in real time. Accordingly, the present invention
contemplates the use of an alternative quantization process to VQ process
46c when a slowest subframe rate is selected. Consequently, the format
described by FIG. 4E describes 1 bit allocated to synchronization and 2
bits allocated to subframe rate as discussed above in FIG. 4A. However,
FIG. 4E allocates only 9 bits to an excitation field and 6 bits to an
energy field. In FIG. 4E, the spectrum field requires 36 bits.
Referring back to FIG. 3, process 50 formats data into various base frame
formats, as described in FIGS. 4. The base frame rate remains constant and
the bit rate remains constant. However, such formats contemplate a
variation in subframe rates through the selection of base frame formats.
Process 50 applies formatted base frames of data to fixed rate channel 18
at the completion of analysis process 31.
Synthesis process 51 receives base frames of data formatted by process 50
and decompresses this data to synthesize voice data samples. Synthesis
process 51 is performed in vocoder 16b (see FIG. 2). It represents the
inverse of the above-described analysis process.
In a "get subframe rate" process 52, the subframe rate field, described
above in connection with FIGS. 4, from the base frame of data is obtained
and output to other processes within synthesis process 51.
An excitation expansion process 54 represents a conventional process which
reverses excitation quantization process 38 from analysis process 31. This
process operates on data obtained from the excitation field of the base
frame. In the preferred embodiment, one excitation field applies to all
subframes. Thus, the output from excitation expansion process 54 applies
to all subframes contained in a base frame.
An energy expansion process 56 receives the base frame of data, obtains the
energy fields, and performs a conventional expansion process to obtain a
unique energy value associated with each of the subframes contained within
the base frame of data. Accordingly, an independent energy predictor code
is provided at the output of energy expansion process 56 for each of the
subframes within the base frame of data.
A spectrum expansion process 58 receives the base frame of data and
transforms the code contained within the spectrum field into a set of LPC
coefficients. Since the present invention contemplates vector
quantization, spectrum expansion process 58 contemplates an inverse vector
quantization operation for expansion of the quantization caused by
spectrum quantization process 42 in analysis process 31. Accordingly, a
switching step 60 selects only one of a plurality of expansion tasks 62 to
operate upon the spectrum data obtained from the base frame.
Switching step 60 selects VQ task 62a when subframe rate data obtained from
the base frame indicates a maximum subframe rate for the base frame of
data. VQ task 52 performs an inverse vector quantization operation to
obtain an independent set of predictor code spectrum coefficients for each
of the subframes within the base frame of data. The inverse vector
quantization operation represents a simpler operation than the vector
quantization operation. This task resembles a table lookup operation
utilizing the same codebook as was used by VQ task 46a in analysis process
31.
Likewise, switch 60 selects VQ task 62b when the subframe rate data from
the base frame of data suggests a medium subframe rate within the base
frame. Additionally, switch 60 selects task 62c for expansion of a base
frame of data that contains only a single subframe.
Although the vector quantization operations utilized in analysis process 31
and the inverse quantization processes utilized by synthesis process 51
may require a large amount of memory for the codebooks utilized therewith,
the same memory may be used for both analysis and snythesis processes.
Accordingly, when the same or identical vocoders are utilized to transfer
data through fixed rate channel 18, codebooks need not be duplicated for
synthesis and analysis operations.
An LPC synthesis process 66 obtains predictor coefficient inputs from each
of excitation expansion process 54, energy expansion process 56, and
spectrum expansion process 58. LPC synthesis process 66 performs a
conventional LPC synthesis operation for each of the subframes indicated
by process 52. Thus, as discussed above in connection with LPC analysis
process 36, LPC synthesis process 66 performs one or more synthesis
operations over the base frame of data. The output from LPC synthesis
process 66 represents a multiplicity of voice data samples. In the
preferred embodiment, LPC synthesis 66 produces 180 samples every 22.5
milliseconds as shown at completion state 68 in FIG. 3.
Accordingly, the present invention utilizes a general purpose vocoder
architecture to implement a variable frame rate, constant bit rate vocoder
without the use of buffering or feedback schemes to maintain the constant
bit rate. Rather, the constant bit rate is established through the use of
a constant base frame rate. A subframe rate is modulated by spectral
change of an analog voice signal being analyzed. The spectral change
identifies whether a given sound resembles a vowel or a consonant.
The present invention is described above with reference to a particular
preferred embodiment which facilitates teaching the present invention.
Those skilled in the art will recognize that many alternative embodiments
also fall within the scope of the present invention. For example, a wide
variation in the number of samples per frame, length of base frames, and
particular formats of base frames are contemplated within the scope of the
present invention. Likewise, a wide variation may occur in the particular
vocoder structures utilized to implement the method of the present
invention. These and other modifications to the preferred embodiment which
are obvious to those skilled in the art are intended to be included within
the scope of the present invention.
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