Language modelling and english speech prediction system to aid people with stuttering disorder

Abstract

This paper proposes a novel method to predict the speech based on N-Gram language model for English Language. It also concentrates on how Speech Completion can be combined with stuttering detection to aid people suffering from this disorder to overcome psychological and social introversion. To the best of our knowledge, such systems exist only in Japanese language and hence, this paper is the first to introduce such an application for English language. The existing work in Japanese language uses a vocabulary tree structure for prediction in contrast to the n-gram language model used in this paper. The basic idea of the proposed work is to consider the user's speech input for detecting the repetition of words as stuttering. If this repetition of words is detected then, the next word can be predicted after eliminating the repeated word using the n-gram language model and the predicted word can be converted back to speech. Using this proposed methodology, we are able to achieve a prediction accuracy of 87% when a 10-fold test is carried out. � 2015 ACM.