Improved Wave-U-Net algorithm for cochlear implants
GONG Jinqi
YE Ping
WU Yifan
CHANG Zhaohua
FAN Wei
XU Changjian
Abstract：Aim at poor speech perception in noisy environments by cochlear implant users and the inadequacy of existing noise re-duction algorithms,we proposed an improved Wave-U-Net model.By adopting lightweight convolution,introducing attention mecha-nism,improving loss function,and optimizing dataset structure,the noise reduction effect of cochlear implants was enhanced.Using short-time objective intelligibility(STOI),perceptual evaluation of speech quality(PESQ),floating point operations per second(FLOPs),and Params to evaluate the noise reduction effect and complexity of the model,which reached 0.81,2.75,0.83 G,and 1.04 M,respectively.The experimental results showed that our algorithm achieved obvious noise reduction effect while conformed to the specifications of cochlear implant products,improved the speech perception effect of cochlear implant users in complex noise environ-ments.The results provide new possibilities for the improvement of cochlear implant algorithms and can offer better auditory experience for patients with hearing impairment.
Keywords：Cochlear implantImproved Wave-U-NetNoisy environmentSpeech perceptionSpeech noise reduction
Publication Date：2024-02-28
Online Publishing Date：2026-09-11(First online date of this platform, not the publication date of the document)
Pages：8( 62-69 )