Open AccessIdentifying Stuttering using Deep learning
Author(s) -
Vedant Tibrewal*,
Alok Pandey,
Mohammed Mobasserul Haque,
M. Manimozhi
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.j9077.0981119
Subject(s) - stuttering , fluency , affect (linguistics) , psychology , audiology , speech production , variety (cybernetics) , cognitive psychology , speech recognition , computer science , developmental psychology , medicine , artificial intelligence , communication , mathematics education
Stuttering is a prevalent neurodevelopmental speech disorder, wherein people suffer from disfluencies in speech production. Speech disorders such as stuttering affect a variety of other communication problems such as hearing and fluency. Common therapies of stuttering involve strategies to minimize stuttering but do not attempt to eliminate stuttering, Researchers have analyzed the root cause of stuttering tends to be neurological roots. Therefore, there needs to be a more generic therapy technique which is more adaptive. This paper proposes a deep learning and neural network-based algorithm for adaptive neurological stuttering by utilizing the potential of mirror neurons