  Achieving and maintaining the performance of ubiquitous (Automatic Speech
Recognition) ASR system is a real challenge. The main objective of this work is
to develop a method that will improve and show the consistency in performance
of ubiquitous ASR system for real world noisy environment. An adaptive
methodology has been developed to achieve an objective with the help of
implementing followings, -Cleaning speech signal as much as possible while
preserving originality / intangibility using various modified filters and
enhancement techniques. -Extracting features from speech signals using various
sizes of parameter. -Train the system for ubiquitous environment using
multi-environmental adaptation training methods. -Optimize the word recognition
rate with appropriate variable size of parameters using fuzzy technique. The
consistency in performance is tested using standard noise databases as well as
in real world environment. A good improvement is noticed. This work will be
helpful to give discriminative training of ubiquitous ASR system for better
Human Computer Interaction (HCI) using Speech User Interface (SUI).
