A Supervised Speech Enhancement Method for Smartphone-Based Binaural Hearing Aids

It is essential but quite challenging to alleviate speech information loss and distortion while developing the speech processing algorithms in hearing aids. Recently, many speech enhancement methods based on deep learning are proven effective. However, most of the algorithms fail to achieve real-time processing, which is significant for hearing aids, especially for a smartphone-centered binaural hearing aid system. A supervised speech enhancement method based on an RNN structure is proposed to address the real-time problem. The problem is explored as a resource-constrained speech intelligibility improvement problem with the target of improving speech intelligibility at low SNR situations. The objective experimental result using the standard evaluation metrics has verified the superiority of the proposed method. The trial use by a small number of volunteers also indicates that the user experience has been improved with the proposed method.