### XE31CZS Exercise - Linear Prediction Analysis (LPC) - LPC Spectrum

• Compare short-time spectrum estimation using DFT and LPC analysis
• For the evaluation of algorithm use voiced part of speech vm0.bin.

• AR cofficients of the signal could be computed using fcn lpc. Parameters of AR model will be p=16, N = 512
• LPC spectrum is given as frequency response synthesizing filter ( fcn freqz )
• Draw both short-time spectrum estimations (DFT and LPC) into one plot for comparison !!
• Observe influence of wieghting of analyzed signal by Hamming window.
• Observe influence of LPC spectrum on amplification parameter G.

• Compare G or E_p respectively evaluated as:
• output of fcn lpc,
• by the formula from AR and autocorrelation coefficients,
• by the direct evaluation of power of error signal.
• Observe the results for different order of AR model p=16, 10, 6. Explain the results !!

• Example: Compare possible spectral resolution in spectral analysis using DFT aan LPC.
• Choose optimal order of AR model for particular task specified bellow.
• Evaluate spectral estimation from follwoing number of samples: N=64 and N= 256.
• Use weigthing of the signal by Hamming window.

• sinusoidal: f=13 Hz, fs= 100 Hz
• 2 sinusoidals of close frequencies: f1=13 Hz, f2=15 Hz, fs= 100 Hz