Deep learning algorithms have influenced various areas, even natural processing language (or speech recognition), which has led them to be utilized to enhance technologies’ performances for the hearing-impaired population. In this report of the reviewed literature, challenges and limitations in recognizing speech for the hearing-impaired group were identified. It is to determine the reason for applying deep learning algorithms in speech-enhancing technologies. The study utilized a systematic literature review by assessing studies from 2018 to 2024 of deep learning algorithms in recognizing speech from reliable and credible online databases. About 200 accumulated studies were evaluated, and 18 finalized articles were selected for further analysis. The study examined various challenges to existing speech enhancement technologies, wherein environmental noise was identified as the major problem for accurately recognizing speech. These led to the application of different deep learning algorithms, including speech intelligibility algorithms for denoising systems, and improving the existing hearing aid and cochlear implant technology with better user experience. By increasing speech recognition accuracy, deep learning algorithms improve the quality of social environments and facilitate communication with hearing-impaired individuals in noisy settings. Deep learning continuously expands the speech recognition systems’ capabilities, eventually benefiting the hearing-impaired community by increasing communication accessibility and quality of life.