This threshold depends upon the frequency, the type of masker, and the kind of sound being masked.
In the context of audio transmission, there are some advantages to being unable to perceive a sound.
This requires fewer bits to encode the sound and reduces the size of the final file.
In this situation, it would be necessary to compute the global masking threshold using a high resolution Fast Fourier transform via 512 or 1024 points to determine the frequencies that comprise the sound.
Because there are bandwidths that humans are not able to hear, it is necessary to know the signal level, masker type, and the frequency band before computing the individual thresholds.