  The main motivation for Automatic Speech Recognition (ASR) is efficient
interfaces to computers, and for the interfaces to be natural and truly useful,
it should provide coverage for a large group of users. The purpose of these
tasks is to further improve man-machine communication. ASR systems exhibit
unacceptable degradations in performance when the acoustical environments used
for training and testing the system are not the same. The goal of this research
is to increase the robustness of the speech recognition systems with respect to
changes in the environment. A system can be labeled as environment-independent
if the recognition accuracy for a new environment is the same or higher than
that obtained when the system is retrained for that environment. Attaining such
performance is the dream of the researchers. This paper elaborates some of the
difficulties with Automatic Speech Recognition (ASR). These difficulties are
classified into Speakers characteristics and environmental conditions, and
tried to suggest some techniques to compensate variations in speech signal.
This paper focuses on the robustness with respect to speakers variations and
changes in the acoustical environment. We discussed several different external
factors that change the environment and physiological differences that affect
the performance of a speech recognition system followed by techniques that are
helpful to design a robust ASR system.
