Individualized speech enhancement for hearing-impaired listeners

Despite significant progress in speech enhancement (SE), improving speech intelligibility and perceptual quality in noisy environments for hearing-impaired individuals remains challenging. This paper presents an individualized speech-enhancement (ISE) framework that integrates noise reduction (NR) and sound amplification for hearing loss compensation within a unified system. Our fully differentiable, closed-loop design incorporates biophysically realistic auditory models. The framework features two pathways: one simulating the auditory response of a normal-hearing (NH) system to denoised speech and the other modeling a hearing-impaired (HI) system's response to noisy speech. The ISE model is trained by minimizing the difference between NH and HI auditory responses. Experimental results show that the ISE model enhances speech intelligibility and perceptual quality in noisy conditions for HI listeners, offering a promising foundation for advancing personalized noise reduction strategies.