TITLE:
Addressing Hearing Impairments through Machine Learning: A Review of Sound Detection and Assistive Technologies
AUTHORS:
Nada Barnawi, Mohammed Alnuem
KEYWORDS:
Machine Learning-Based, Deaf and Hard of Hearing, Sound Detection, Assistive Technologies, Speech Recognition, Realtime
JOURNAL NAME:
Open Journal of Applied Sciences,
Vol.15 No.8,
August
21,
2025
ABSTRACT: This paper studies recent assistive technologies and AI sound detection systems that have been developed to support both the safety and communication of individuals who are deaf. It highlights how modern sound detection systems effectively address challenges such as real-time processing and polyphonic audio environments, while integrating speech recognition to improve situational awareness and interaction. The findings confirm that these technologies not only increase auditory accessibility but also empower greater independence and security for deaf and hard-of-hearing users in everyday environments.