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@article{169267,
        author = {Manupati Jaideep},
        title = {Augmentative Alternative Communication and Text-to-Speech for Dyslexia, Autism, and Parkinson’s using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {1180-1186},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169267},
        abstract = {In the context of addressing communication challenges faced by individuals with diverse neurodevelopmental and neurological disorders, this project focuses on the development of an advanced speech synthesis system. Leveraging state- of-the-art technologies such as Convolutional Neural Networks (CNN) and Long Short-Term Memory Recurrent Neural Net- works (LSTM-RNN), the system is designed to produce natural and intelligible synthetic speech. This initiative is especially crucial for individuals dealing with visual impairment, Dyslexia, Parkinson’s disease, Autism Spectrum Conditions (ASC), and Amyotrophic Lateral Sclerosis (ALS). The proposed system aims to enhance communication accessibility and effectiveness for those with specific cognitive and motor challenges, contributing to a more inclusive and supportive digital environment.},
        keywords = {},
        month = {November},
        }