Summary: You will write MATLAB code to compute the autocorrelation sequence of a simple signal. Then you will implement the Levinson-Durbin algorithm in MATLAB and analyze a recording of your own voice.
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First, take a simple signal (e.g., one
period of a sinusoid at some frequency) and plot its
autocorrelation sequence for appropriate values of
xcorr MATLAB
function to compare with your own version of this function.
At what time shift
Next, write your own version of the Levinson-Durbin algorithm
in MATLAB. Note that MATLAB uses indexing from
Apply your algorithm to a
.wav audio files on the PC using Sound
Recorder or a similar application. Typically, a sample rate
of
wavread,
wavwrite, sound will help you read,
write and play audio files in MATLAB:
The output of the algorithm is the prediction coefficients
levinson or
lpc functions available in the MATLAB toolbox.
Next, plot the frequency response of the IIR model represented
by the LPC coefficients (see Speech Processing: Theory of LPC Analysis and
Synthesis). What is the fundamental frequency of the
speech segment? Is there any similarity in the prediction
coefficients for different
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