  Dysarthria is malfunctioning of motor speech caused by faintness in the human
nervous system. It is characterized by the slurred speech along with physical
impairment which restricts their communication and creates the lack of
confidence and affects the lifestyle. This paper attempt to increase the
efficiency of Automatic Speech Recognition (ASR) system for unimpaired speech
signal. It describes state of art of research into improving ASR for speakers
with dysarthria by means of incorporated knowledge of their speech production.
Hybridized approach for feature extraction and acoustic modelling technique
along with evolutionary algorithm is proposed for increasing the efficiency of
the overall system. Here number of feature vectors are varied and tested the
system performance. It is observed that system performance is boosted by
genetic algorithm. System with 16 acoustic features optimized with genetic
algorithm has obtained highest recognition rate of 98.28% with training time of
5:30:17.
