The ideal binary time-frequency masking is a signal separation technique that keeps the mixture energy in the time-frequency units where local SNR (Signal-to-Noise Ratio) exceeds a certain threshold and rejects mixture energy in other time-frequency units. A binary mask is defined in time-frequency domain as a matrix of binary numbers, and the elements of the speech signal in time-frequency domains are referred to as T-F units, through this mask, the frequency band of the received signal is decomposed (simulating the human acoustic system) by using special filters, and the energies of the signal are computed in the time domain. The IBM would compare the SNR within each T-F unit with a threshold of units of the target signal in dB, the units with SNR exceeding the threshold would be signed as 1, otherwise as 0. The IBM gain from the segregated signal would be applied again to the mixture of target speech and noise. Some experiments studied the effect and results of the binary masking approach for normal hearing and hearing-impaired subjects, in this research work, we submitted an experiment done by (Di Lang Wang, 2009) to prove the effect of the IBM on the Speech-reception Threshold SRT for Normal and Hearing-Impaired listeners, as well as, discuss the results of the experiment and how the IBM effectively improved the speech intelligibility specially for the Hearing-Impaired individuals in the Cafeteria Background noise, the results also proved that the Speech intelligibility has improved in the low-frequency region by the IBM more than the high-frequency region. In the future work we would discuss the integration of the IBM technique within the cochlear implants.