Figure 3 Frame blocking of the speech signal-Development an Automatic Speech to Facial Animation Conversion for Improve Deaf Lives

<p>The next frame will begin M samples (i.e. 156 samples) after the first frame, and it will<br> overlap the first frame by N-M samples (256 &ndash; 156 = 100 samples). Then the third frame will start<br> at 2M samples after the first frame and it will overlap first frame by N-2M. The fourth frame will<br> start at 3M samples after the first, and it will overlap it by N-3M. The process will continue until all<br> input signal is accounted for. The result of this step plotted using MATLAB plot command and<br> displayed in Figure 3.<br> Figure 3 Frame blocking of the speech signal<br> The next step in the processing is to window each individual frame so as to minimize the<br> signal discontinuities at the beginning and end of each frame. The concept here is to minimize the<br> spectral distortion by using the window to taper the signal to zero at the beginning and end of each<br> frame. If we define the window as w(n), 0 &le; n &le; N &minus;1, where N is the number of samples in each<br> frame, then the result of windowing is the signal<br> y (n) = x (n)w(n), 0 &le; n &le; N &minus;1 l l<br> &nbsp;</p>