International Research Journal of Education and Technology

Auditory scene analysis is a crucial aspect in the design of digital hearing aids. The goal of ASA is to separate and identify sounds in complex acoustic environments. This paper presents a deep learning based sound classification approach for ASA in digital hearing aids. The proposed method uses convolutional neural networks to classify sounds in real-time. Experiments were conducted on a publicly available dataset and the results demonstrate that the proposed method outperforms traditional deep learning algorithms. This study shows the potential of deep learning in improving the performance of ASA in digital hearing aids and provides a foundation for further research in this area.

Keywords-- Hearing aids, sound classification, auditory scene analysis, Convolution Neural Network.