A Smart Binaural Hearing Aid Architecture Leveraging a Smartphone APP With Deep-Learning Speech Enhancement

被引:6
|
作者
Li, Yingdan [1 ]
Chen, Fei [1 ]
Sun, Zhuoyi [2 ]
Ji, Junyu [3 ]
Jia, Wen [4 ]
Wang, Zhihua [5 ,6 ]
机构
[1] Tianjin Univ, Sch Microelect, Tianjin Key Lab Imaging & Sensing Microelect Tech, Tianjin 300072, Peoples R China
[2] Tsinghua Univ, Inst Microelect, Beijing 100084, Peoples R China
[3] Shenzhen Zhiting Technol Co Ltd, Shenzhen Eartech Co Ltd, Shenzhen 518100, Peoples R China
[4] Tsinghua Univ Shenzhen, Res Inst, Shenzhen 518057, Peoples R China
[5] Tsinghua Univ, Inst Microelect, Tsinghua Natl Lab Informat Sci & Technol, Beijing 100084, Peoples R China
[6] Tsinghua Univ, Res Inst, Shenzhen 518057, Peoples R China
关键词
Binaural hearing aids; smartphone; real-time se app; e-health; deep learning; RECOGNITION; DESIGN; NOISE;
D O I
10.1109/ACCESS.2020.2982212
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a smartphone-based binaural hearing aid architecture for improving the speech intelligibility of hearing aid users. The proposed system consists of an earpiece, a smartphone and an application that performs real-time speech enhancement. The speaker & x2019;s voice, which is picked up by the microphone of the earpiece that is worn on the ear, is transmitted to the smartphone via wireless technology. After the speech intelligibility is improved in real time by the deep learning speech enhancement application, it is returned to the earpiece and generates sound. Deep learning speech enhancement algorithms can be used without performing burdensome calculations on the processors in the hearing aid. The results showed that the average usage of the central processing unit in the smartphone was approximately 26 & x0025;, and the signal-to-noise ratios improve by at least 20 & x0025;. The presented objective and subjective results show that the proposed method achieves comparatively more noise suppression without distorting the audio.
引用
收藏
页码:56798 / 56810
页数:13
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