Suppose that we have audio signal x[n].

2. Filter the Voice Signal (a) Create a low pass filter h[n] to process your voice signal x[n]. You can use a moving average FIR filter with the window size windowSize. You may change the window size. (b) Filter your voice signal x[n] by the filter h[n] to get y[n]. Use the filter function filter(). (c) Plot the voice signals and filter, x[n], h[n], and y[n] in a figure window. (d) Plot the frequency spectrums of the signals and the filter. (e) Listen to the original voice x[n] and the filtered voice y[n] and compare them. You can use the sound() function to listen to the voice signal. (f) Save the signals into .wav audio files. Use the function audiowrite(). 2. Filter the Voice Signal (a) Create a low pass filter h[n] to process your voice signal x[n]. You can use a moving average FIR filter with the window size windowSize. You may change the window size. (b) Filter your voice signal x[n] by the filter h[n] to get y[n]. Use the filter function filter(). (c) Plot the voice signals and filter, x[n], h[n], and y[n] in a figure window. (d) Plot the frequency spectrums of the signals and the filter. (e) Listen to the original voice x[n] and the filtered voice y[n] and compare them. You can use the sound() function to listen to the voice signal. (f) Save the signals into .wav audio files. Use the function audiowrite()