Abstract
Abstract: A total of 63 million people in India have hearing impairment, which is a common cause of disability. Due to communication barriers, these individuals are at risk for reduced cognitive skills and language deficits which may contribute to their poor general and oral health. Instructing these individuals regarding oral health concerns, treatment options and prognosis is often challenging for dental professionals. An Automatic Speech to Sign Language Translation Software (ASSiST) was developed to improve brushing technique among children with hearing impairment. The programming of Automatic Speech Recognition (ASR) system was done using Linear Predictive coding (LPC) algorithm for extraction of Speech Signals and Artificial Neural Networks as a classifier and recognizer. This tool is tested to help imparting oral hygiene instructions in the form of a sequence-based brushing technique to the children chair side which when spoken by the dentist translates it into the respective regional sign language which is displayed on the screen.
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