DESIGN OF VLSI CHIP FOR
VOICE COMPRESSION
M. KUMARASAMY COLLEGE OF ENGINEERING
KARUR.
Name:
R.ANITHA,A.NANDHINI
Program & Dept.:
B.E. (ECE)
E- Mail id:
Year/Sem
anithamalar2010@gmail.com
:
III/VI
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method of converting higher level
ABSTRACT:
Abstraction to lower level and to
The aim of this paper is to
generate the gate level circuit of the
design a VLSI CHIP FOR VOICE
COMPRESSION;
the
chip. The chip thus designed can be
designing
used for various applications like
process involves the conversion of
cell phones for voice transmission
the analog voice signal into digital
and can be used in the computer
form of 14 bits and compression of
the
later
into
8bits.
networks.
ASIC
methodology of design is followed
PROBLEM DEFINITION:
in this process; the purpose of the
The goal of this VLSI is
compression is due to two main
to
factors of data transfer rate and data
design
compression
storage. In the compressed digitized
programming
voice signal the number of bits for
a
chip
using
for
voice
the
VHDL
method.
The
advantage of the compression is
representation is very less so that
that increasing the transfer rate of
the data transfer rate is very high
the voice signal and also to reduce
and also causes very less storage
the space for the storage. Thus
amount for the voice signal.
developed chip can be embedded in
cell phones so that the data transfer
SIMULATION
and
is very high and it can also be
SYNTHESIS process are involved
employed in the computer networks
so that the simulation phase can be
in order to reduce the storage space.
used verification of the validity of
the program and timing diagrams
are used to check the output results.
INTRODUCTION TO VLSI
Synthesis phase is used automatic
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Definition:
A circuit in which many
elements are fabricated and
interconnected on a single chip of
semi conducting material as
INTEGRATED in which
ASIC methodology of design:
transistors, diode, resistors etc are
ASIC method stands
fabricated separately and then
assembled
for application specific
Advantages:
integrated circuit. It allows
• Speed
us design a IC as per the
• Size
required application. It
• Number of applications
provides a comfortable
• Continuous integration of
method of design by
electronic devices.
allowing easy programming
• Progression of IC towards next
methods through software.
technology called VLSI
Steps involved in ASIC method
can be explained with the
following flowchart.
DIGITAL DESIGN METHOD:
There are two types of digital
design
• Standard logic
•Asic method
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STEPS TO DESIGN VLSI FOR
VOICE COMPRESSION:
 Conversion of analog signal to
digital of 14 bits.
 Compression of the 14 bits into 8
bits during transmission.
 Decomposition of 8bit digital
signal into 14 bits on the
reception.
 Simulation and synthesis.
CONVERTING ANALOG
SIGNAL INTO DIGITAL:
There are many methods
What is VHDL
used for A/D conversion, the
VHDL stands for very
high
speed
integrated
method used here is COMBO
circuit
CODES .The conversion process
Hardware Description Language. It
can be done using much software
is a programming language used for
such as MATLAB or by using
VLSI design. Used to model a
hardware chip.
VLSI system from algorithmic
COMBO CODES:
level to gate level.
Basics:
Goals of VHDL:
Pulse
 Designer to describe complex
code
modulation
(PCM) is a method of digitizing or
circuits using programming.
quantizing an analog waveform that
 Provide standard format for
is
VHSIC design.
used
primarily
in
the
transmission of speech signals, for
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example
in
telephone
In
any
sampled
data
communication. In theory this error
system, the analog _to _digital
can
(A/D)
be
made
significant
by
conversion
Process
representing the estimate with a
introduces quantization noise. For
large number of bits. The goal is to
the usual linear A/D encoding
quantize the data in the smallest
scheme, the Digitalized code word
number of bits that results in a
is a truncated binary representation
tolerable error. In the case of
of the analog sample. The effect of
speech signal a linear quantization
this truncation is most pronounced
with 13 or 14 bits is the minimum
for small signals.
required
to
produce
a
digital
For voice transmission,
representation of the full range of
this is undesirable since most
speech signals accurately.
information in speech signals
The number of
typically requires a wide dynamic
bits required is reduced to eight in
range. This can be remedied by
the CCITT recommendation G.711
adjusting the size of the
by
quantization interval so that it is
exploiting
a
non-linear
characteristic of human hearing.
proportional to the input signal
The human ear is more sensitive to
level. In this case, the quantization
quantization function to adjust the
interval is small for amplitude
data size in proportion to the input
signals and larger for larger signals.
signal. Thus, smaller signals are
Consequently, lower amplitudes are
approximated
represented with more quantization
with
greater
precision.
levels and, therefore with greater
resolution.
COMPANDING:
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choice for the µ_law companding
CHARACTER SIGNAL
parameter.
This
companding
characteristic exhibits the valuable
of being closely approximated by a
set of eight straight line segments,
as shown in figure. This figure
illustrates how to input the sample
value of segment is exactly one half
* This is the bit pattern transmitted
that of proceeding one. This step
for positive input values. The
size between adjacent code word is
leftmost bit is a 0 for negative
doubled
input values.
segment.
in
each
succeeding
The resulting encoding scheme is
logarithmic in nature and has the
property of yielding the greatest
dynamic range for a given signal to
noise ratio and word length
.Companding is defined by two
international standards based on
this relation they are µ-255
companding and A law
companding.
µ-255 companding:
Eight
sign
µ_255 law companding and is
magnitude
given by the equation
words can represent 255 different
F(x)=sgn(x)ln(1+µ„ x„ )/ln(1+µ)
code words. This made 255 the
most
approximated
Where:
convenient
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F(x) is the compressed output value
The encoding algorithm is best
x is the normalized input
understood by examining the
signal(between (-1and 1)
segment end points of the table
µ is the compression parameter
below
(=255 in North America)
which begin with the values
Sgn(x) is the sign (+/-) of x
31,95,223,…...4063.
Signals tend to be more numerous
Note that 31=2^6 -33
than
large
amplitude
samples.
95=2 ^7-33
Consequently, inverting the bits to
223=2^8 -33
increase the density of positive
4063 =2 ^9 -33
pulse on the transmission lines,
So that if 33 is added to each value
which improves the performance of
in the table , the end points become
timing and clock recovery circuits
powers of two.
This means that the segment
number corresponding to a number
ALGORITHM:
Unfortunately
sign
quantized
_magnitude
14_bit
numbers
N (which is to be encoded) can be
are
determined by finding the most
compressed of 8_bit Signed µ_255
significant ‘1’bit in the binary
code words expanded to their
representation of N+33.
original amplitude. The code word
On expansion, these lost
Y, formed by Compression, has the
bits are assumed to have been the
format Y=PSSSQQQQ composed
median of the possible numbers
of:
which these lost bits could have
Polarity bit: P
represented a one followed by
3_bit sign segment numbers: SSS
zeros. This rounding limits the loss
4_bit quantization bit number:
in accuracy.
QQQQ
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For example consider the 8_bit
format as
01011010
Here
• This table displays magnitude
encoding only. Polarity bits are
assigned as”0” for positive and “1”
*This polarity is not shown in this
for negative. In all transmission bits
table, the leading bit is the sign bit,
are inverted.
which is not shown.
EXAMPLE
FOR
COMPRESSION:
EXAMPLE
FOR
DECOMPRESSION:
• This polarity is not shown in this
table and the leading bit, which is
not shown, is the sign bit.
IMPLEMENTATION:
Step 1: Read the data from the file
where the amplitudes are stored.
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Step 2: extract the integer part
another file with all the sign bits
alone from the data and also save
and decimal point
the sign magnitude of it.
.FUTURE ENHANCEMENT
Step 3: add 33 to the input data by
Further expansion of this
using the simple full adder logic for
problem includes the problem of
biasing the sample.
doing encryption and decryption of
Step 4: now assign the segment
the voice signals. The voice signal
code of the data by checking the
can be encrypted after the
data from it’s MSB.
compression and it can be
Eg: for the segment 7 the data
transmitted and from the reception
format will be
side. The signal can be decrypted.
1 q3 q2 q1 q0xxxxxxxx
Public and private key algorithm
By checking the MSB alone we can
can be used for this process.
decide the segment code.
The wave forms output will be
For segment 6
shown as,
0 1 q3 q2 q1 q0xxxxxxx
By checking the two bit from the
MSB we decide the segment 6 and
so on.
Step 5: After assigning the segment
code we have to assign the code
value by checking the
segment number as shown in the
previous table.
Step 6: This compressed data will
be converted again to decimal
equivalent and then stored in
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types of chip can be obtained by
using the synthesis toll in the
synthesis phase.
REFRENCES:
* VHDL Design by DOUGLES
PERRY
* Communication systems by
SIMON HAYKINS.
CONCLUSION:
The design of VLSI chip
for voice compression can be
effectively implemented using the
above
mentioned
compression
algorithm. The outputs can be
verified by using the simulation
phase and logical view of various
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