Based on the results, the maximum frequency that would not be aliased was the Nyquist frequency, which was 5000 Hz. In addition to that, the amplitude of the loud voice was higher than the amplitude of the low voice. The number of bits calculated based on the quantization was equal to 9.97 bits. The high cutoff and the low cutoff which are 110 Hz and 1100 Hz, were used to show the Fast Fourier Transform of the filtered voices, which results in producing better voice of the recording. Based on the FFT graphs, the amplitude of the 440 Hz was the highest at the same peak, and that is why the sound was directly clear, and that proves that the played sound was with the frequency of 440 Hz. For the low and loud frequency, the graph showed the background noise recorded with the voice signal.

The use of the decimating factor is that it will resample the recorded voice signal at a lower sampling frequency. Therefore, by changing the value of the decimating factor, the between 1 to 8, the sounds became more clear and recognizable. That is because the decimating factor, decrease the sample rate and increase the frequency of the voice signal in order to avoid the signal to be aliased. Based on research, the …show more content…
Higher frequency response can help to differentiate the voice recorded outside when the signal being filtered. The too low sampling rate will lead to aliasing, which is the loss of the information. To avoid aliasing issue, the signal being recorded must be less than the value of the Nyquist frequency. The too high sampling rate, which can be twice the frequency of the recorded signal would lead to eliminating the effects of aliasing. However, it will require more samples to be recorded and will cause some difficulties in the storage