Design and Integration of Alert Signal Detector and Separator for Hearing Aid Applications.

ABSTRACT: Alert signals like sirens and home alarms are important as they warn people of precarious situations. This work presents the detection and separation of these acoustically important alert signals, not to be attenuated as noise, to assist the hearing impaired listeners. The proposed method is based on convolutional neural network (CNN) and convolutional-recurrent neural network (CRNN). The developed method consists of two blocks, the detector block, and the separator block. The entire setup is integrated with speech enhancement (SE) algorithms, and before the compression stage, used in a hearing aid device (HAD) signal processing pipeline. The detector recognizes the presence of alert signal in various noisy environments. The separator block separates the alert signal from the mixture of no

SUBMITTER: Bhat GS 

PROVIDER: S-EPMC7423022 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature