  Acoustical mismatch among training and testing phases degrades outstandingly
speech recognition results. This problem has limited the development of
real-world nonspecific applications, as testing conditions are highly variant
or even unpredictable during the training process. Therefore the background
noise has to be removed from the noisy speech signal to increase the signal
intelligibility and to reduce the listener fatigue. Enhancement techniques
applied, as pre-processing stages; to the systems remarkably improve
recognition results. In this paper, a novel approach is used to enhance the
perceived quality of the speech signal when the additive noise cannot be
directly controlled. Instead of controlling the background noise, we propose to
reinforce the speech signal so that it can be heard more clearly in noisy
environments. The subjective evaluation shows that the proposed method improves
perceptual quality of speech in various noisy environments. As in some cases
speaking may be more convenient than typing, even for rapid typists: many
mathematical symbols are missing from the keyboard but can be easily spoken and
recognized. Therefore, the proposed system can be used in an application
designed for mathematical symbol recognition (especially symbols not available
on the keyboard) in schools.
