Final answer:
Option B: The Nyquist-Shannon sampling theorem states that the number of samples required to digitize an analog, it would be 8,000 samples per second or 8,000 bits per second.
Step-by-step explanation:
The Nyquist-Shannon sampling theorem states that in order to properly digitize an analog signal, the sampling frequency must be at least twice the highest frequency component of the signal. In this case, the intelligible human voice occupies a frequency range spanning about 4 kilohertz, so to properly digitize it, we would need a sampling frequency of at least 8 kilohertz (8,000 Hz). Each sample represents a bit of information, so the number of samples required each second to digitize the human voice would be equivalent to the sampling frequency, which is 8,000 samples per second or 8,000 bits per second.
According to the Nyquist-Shannon sampling theorem, to properly digitize an analog signal, the sampling rate must be at least twice the highest frequency contained in the signal. Since an intelligible human voice occupies a frequency range up to about 4 kHz, we need to sample at a minimum rate of 8 kHz to accurately capture the voice signal. Therefore, to digitize a human voice, 8000 samples are required each second.