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For this section download the speech.au file. For instructions on how to load and play audio signals click here .
Digital signal processing is widely used in speech processing for applications ranging from speech compression and transmission,to speech recognition and speaker identification. This exercise will introduce the process of reading and manipulatinga speech signal.
First download the speech audio file speech.au , and then do the following:
auread
command to load the file
speech.au into Matlab.plot
command).sound
function.For this section download the signal1.p function.
In this section you will practice writing .m-files
to calculate the basic attributes of continuous-time signals.Download the function
signal1.p .
This is a pre-parsed pseudo-code file (P-file), which isa “pre-compiled” form of the Matlab function
signal1.m .
To evaluate this function,simply type
y = signal1(t)
where
t
is a vector
containing values of time.Note that this Matlab function is valid for any real-valued time,
t
,
so
y = signal1(t)
yields samples of a continuous-time function.
First plot the function using the
plot
command.
Experiment with different values for the sampling periodand the starting and ending times, and choose values that
yield an accurate representation of the signal.Be sure to show the corresponding times in your plot using a command
similar to
plot(t,y)
.
Next write individual Matlab functions to compute the
minimum, maximum, and approximate energy of this particular signal.Each of these functions should just accept an input vector of times,
t
,
and should call
signal1(t)
within the body of the function.
You may use the built-in Matlab functions
min
and
max
.
Again, you will need to experiment with the sampling period,and the starting and ending times so that your computations of the min, max, and energy are accurate.
Remember the definition of the energy is
Plot the following two continuous-time functions over
the specified intervals. Write separate script files if you prefer.Use the
subplot
command to put both plots in a single figure,
and be sure to label the time axes.
rect(t)
may be computed in Matlab
by using a Boolean expression.For example, if
t=-10:0.1:10
,
then
$y=rect\text{(}t\text{)}$ may be computed using the Matlab command
y=(abs(t)<=0.5)
.Write an .m-script file to stem
the following discrete-time function for
$a=0.8$ ,
$a=1.0$ and
$a=1.5$ .
Use the
subplot
command to put all three plots
in a single figure.Issue the command
orient('tall')
just prior to printing to prevent crowding of the subplots.
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