Task 15: Load "noisyhomer.wav" speech signal and plot it. Play the signal and observe the noise in this signal. Calculate and plot the spectrum of this signal. You will notice that the noise affecting this signal is not a narrow band type interference as in the previous example but a broad-band type noise. It is usually of interest to find out how strong is the signal component compared to noise present in the signal. This measure is known as signal-to-noise ratio (SNR) and is expressed as: SNR(dB) = 10 log where Pisma and Prive represent power of the signal and noise present in the signal respectively, Signal power for N samples long signal sequence x(n) can be calculated using the formula: 1 N-! . ' () Write your own function to calculate the power of signal. Now, use your function and the clean version of Homer Simpson's speech from the file "homer.wav" to estimate the SNR of the noisy version of the signal from "noisyhomer.wav". Task 15: Load "noisyhomer.wav" speech signal and plot it. Play the signal and observe the noise in this signal. Calculate and plot the spectrum of this signal. You will notice that the noise affecting this signal is not a narrow band type interference as in the previous example but a broad-band type noise. It is usually of interest to find out how strong is the signal component compared to noise present in the signal. This measure is known as signal-to-noise ratio (SNR) and is expressed as: SNR(dB) = 10 log where Pisma and Prive represent power of the signal and noise present in the signal respectively, Signal power for N samples long signal sequence x(n) can be calculated using the formula: 1 N-! . ' () Write your own function to calculate the power of signal. Now, use your function and the clean version of Homer Simpson's speech from the file "homer.wav" to estimate the SNR of the noisy version of the signal from "noisyhomer.wav