Real-time Audio Recognition for Hearing Impaired

• Published in: 2024 3rd International Conference on Artificial Intelligence For Internet of Things (AIIoT) pp. 1 - 6
• Main Authors: Peddi, Muralidhar, Vardhan, S H V Harsha, Peddi, Giridhar, Ponnam, Satwik, Rani, C, Rajesh Kumar, M
• Format: Conference Proceeding
• Language: English
• Published: IEEE 03.05.2024
• Subjects: Accuracy; Audio classification; Audio Signal processing; Convolution Neural Networks; MFCCs; Real-time systems; Robustness; Signal processing algorithms; Switches; Training; User experience; Wake Word Detection
• DOI: 10.1109/AIIoT58432.2024.10574757

Audio recognition technology has seen significant advancements in recent years, offering promising solutions to improve communication and accessibility for deaf individuals. This paper explores the landscape of audio recognition technologies tailored specifically for the deaf community. It delves into the challenges faced by deaf individuals in everyday communication scenarios and how innovative audio recognition systems can mitigate these challenges. The abstract discusses various approaches, including speech-to-text systems, sound recognition algorithms, and real-time captioning tools, highlighting their effectiveness and limitations in facilitating seamless communication for deaf individuals. Furthermore, it examines the integration of machine learning and artificial intelligence techniques in enhancing the accuracy and adaptability of audio recognition systems for diverse environments and user preferences. Additionally, the abstract explores the potential socio-economic impacts of the widespread adoption of audio recognition technologies in empowering deaf individuals, fostering inclusion, and promoting equal opportunities in education, employment, and social interactions.