1
1
Digital Speech Processing—
Lecture 2
Review of DSP
Fundamentals
2
What is DSP?
Analogto
Digital
Conversion
Computer
Input
Signal
Output
Signal
Digitalto
Analog
Conversion
Digital
•
Method to represent a quantity, a phenomenon or an event
•
Why digital?
Signal
•
What is a signal?
–
something (e.g., a sound, gesture, or object) that carries information
–
a detectable physical quantity (e.g., a voltage, current, or magnetic field strength) by
which messages or information can be transmitted
•
What are we interested in, particularly when the signal is speech?
Processing
•
What kind of processing do we need and encounter almost
everyday?
•
Special effects?
3
Common Forms of Computing
•
Text processing
– handling of text, tables, basic
arithmetic and logic operations (i.e., calculator
functions)
–
Word processing
–
Language processing
–
Spreadsheet processing
–
Presentation processing
•
Signal Processing
– a more general form of
information processing, including handling of speech,
audio, image, video, etc.
–
Filtering/spectral analysis
–
Analysis, recognition, synthesis and coding of real world signals
–
Detection and estimation of signals in the presence of noise or
interference
4
Advantages of Digital Representations
•
Permanence and robustness of signal representations; zero
distortion reproduction may be achievable
•
Advanced IC technology works well for digital systems
•
Virtually infinite flexibility with digital systems
– Multifunctionality
– Multiinput/multioutput
•
Indispensable in telecommunications which is virtually all digital
at the present time
Signal
Processor
Input
Signal
Output
Signal
AtoD
Converter
DtoA
Converter
5
Digital Processing of Analog Signals
•
AtoD conversion:
bandwidth control, sampling and
quantization
•
Computational processing:
implemented on computers or
ASICs with finiteprecision arithmetic
–
basic numerical processing:
add, subtract, multiply
(scaling, amplification, attenuation), mute, …
–
algorithmic numerical processing:
convolution or linear
filtering, nonlinear filtering (e.g., median filtering), difference
equations, DFT, inverse filtering, MAX/MIN, …
•
DtoA conversion:
requantification* and filtering (or
interpolation) for reconstruction
x
c
(
t
)
x
[
n
]
y
[
n
]
y
c
(
t
)
AtoD
Computer
DtoA
6
DiscreteTime Signals
{ [ ]},
( ),
,
[ ]
(
),
A sequence of numbers
Mathematical representation:
Sampled from an analog signal,
at time
is called the
and its recipr
a
a
x
x n
n
x
t
t
nT
x n
x
nT
n
T
=
− ∞ <
< ∞
=
=
− ∞ <
< ∞
sampling period,
±
±
±
±
1/
,
8000
1/ 8000
125
sec
10000
1/10000
100
sec
16000
1/16000
62.5
sec
20000
1/ 20000
50
sec
ocal,
is called the
Hz
Hz
Hz
Hz
S
S
S
S
S
F
T
F
T
F
T
F
T
F
T
μ
μ
μ
μ
=
=
↔
=
=
=
↔
=
=
=
↔
=
=
=
↔
=
=
sampling frequency
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2
Speech Waveform Display
7
plot(
);
stem(
);
8
Varying Sampling Rates
Fs=8000 Hz
Fs=6000 Hz
Fs=10000 Hz
Varying Sampling Rates
9
Fs=8000 Hz
Fs=6000 Hz
Fs=10000 Hz
Quantization
in
out
0.3
0.9
1.5
2.1
2.4
1.8
1.2
0.6
7
6
5
4
3
2
1
0
A 3bit uniform quantizer
Quantization:
•
Transforming a continuously
valued input into a
representation that assumes
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 Fall '08
 Rabiner,L
 Digital Signal Processing, Frequency, sampling rate, jω

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