The necessary MATLAB software for computer simulations and the speech/audio files (Ch4Sp8.wav, Ch4Au8.wav, and Ch4Au16.wav) can be obtained from the Book website.

4.5. Linear predictive coding (LPC)

  1. Write a MATLAB program to load, display, and play back speech files. Use Ch4Sp8.wav for this computer exercise.
  2. Include a framing module in your program and set the frame size to 256 samples. Every frame should be read in a 256 × 1 real vector called Stime. Compute the fast Fourier transform (FFT) of this vector, i.e., Sfreq = fft(Stime). Next, compute the magnitude of the complex vector Sfreq and plot its magnitude in dB up to the fold-over frequency. This computation should be part of your frame-by-frame speech processing program.

Deliverable 1:

Present at least one plot of time and one corresponding plot of frequency-domain data for a voiced, unvoiced, and a mixed speech segment. (A total of six plots – use the subplot command.)

c. Pitch period and voicing estimation: The period of a strongly voiced speech signal is associated in a reciprocal manner to the fundamental frequency of the corresponding harmonic spectrum. That is, if the pitch period is T, the fundamental frequency is 1/T. Note that T can be measured in terms of the number of samples within a pitch period for voiced speech. If T is measured in ms, then multiply the number of samples by 1/Fs, where Fs is the sampling frequency of the input speech.

Deliverable 2:

Create and fill Table 4.2 for the first ...

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