AI-Powered Assistive Communication Software for the Deaf
Abstract
The development of AI-powered assistive communication software is crucial for improving interaction for individuals with speech difficulties or those who are deaf. Current Augmentative and Alternative Communication (AAC) devices often experience latency, limiting the effectiveness of real-time communication. This paper explores advanced AI technologies such as real-time speech-to-text conversion, predictive text, and auto-complete functionalities, which are designed to reduce communication delays and enhance fluency. Addition- ally, features like text-to-speech synthesis and image-based communication tools foster more seamless interactions, while environmental sound alerts and sentiment analysis provide contextual awareness. The integration of adaptive learning enables personalized experiences, allowing the software to cater to the unique needs of each user. By leveraging these innovations, the pro- posed system aims to empower individuals with communication impairments, providing them with a more intuitive and independent way to engage with their surroundings and improve their quality of life.
Keywords:
Recurrent Neural Network, Convolution Neural Network
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Copyright (c) 2024 International Journal on Emerging Research Areas
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All published work in this journal is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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