Smart Communication Software for the Hearing Impaired Using Artificial Intelligence
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 NetworkPublished
Issue
Section
License
Copyright (c) 2024 International Journal on Emerging Research Areas

This work is licensed under a Creative Commons Attribution 4.0 International License.
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.
How to Cite
Similar Articles
- Jyothis Joseph , Ajay K Baiju, Ganga Binukumar, Akshara Manoj, Sandra Elizabeth Rony, A Crowd Monitoring and Real-Time Tracking System using CNN , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Tebin Joseph, Pranav Thamban Nair, Sam Kattiveettil James, Mrs Tintu Alphonsa Thomas , Pest Prediction in Rice using IoT and Feed Forward Neural Network , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Abhijith J, Athul Krishna S, Amarthyag P, Angela Rose Baby, Mekha Jose, CATARACT DETECTION USING DIGITAL CAMERA IMAGES , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Amal P Varghese, Simy Mary Kurian, Advancements in ECG Heartbeat Classification: A Comprehensive Review of Deep Learning Approaches and Imbalanced Data Solutions , International Journal on Emerging Research Areas: Vol. 3 No. 2 (2023): IJERA
- Prayag Suresh, Sneha Susan Alex, Rojan Varghese, Thomas Zacharias, Shiney Thomas, Survey of Strabismus Detection Techniques , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Raihana Rasaldeen, Stefi Marshal Fernandez, Irin Rose Jaison, Ria Mariam , A Comparative Study of AI Models and AI-Based Approaches for Evaluating Subjective Answers in Exams , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Jincy Lukose, Anita Ann Joseph, Meenakshy BR , Nevin Siby, Rosaine P Lal , ENHANCED PNEUMONIA DETECTION IN CHEST X-RAYS USING ATTENTION AND FNMS , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Arun Robin, Tijo Thomas Titus, Ms. Minu Cherian, Improved Handwritten Digit Recognition Using Deep Learning Technique , International Journal on Emerging Research Areas: Vol. 3 No. 2 (2023): IJERA
- S Sreejith, Akshara Santhosh, Ardra Haridas, S Jayakrishnan, Ojus Thomas Lee, Chitra Merin Varghese, BrailE- Reading Device for the Deaf and Blind in Real Time Speech , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Charukesh, Ethical Hacking using the Switch Port Analyser in a Enterprise Network , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
You may also start an advanced similarity search for this article.
