Dynamic Processing Neural Network Architecture for Hearing Loss Compensation

Author:

Drgas Szymon1ORCID,Bramsløw Lars2ORCID,Politis Archontis3ORCID,Naithani Gaurav3ORCID,Virtanen Tuomas3ORCID

Affiliation:

1. Institute of Automatic Control and Robotics, Poznan University of Technology, Poznan, Poland

2. Eriksholm Research Center, Snekkersten, Denmark

3. Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland

Funder

subvention financial means

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Acoustics and Ultrasonics,Computer Science (miscellaneous),Computational Mathematics

Reference42 articles.

1. Fluctuation contrast and speech-on-speech masking: Model midbrain responses to simultaneous speech;carney;Proc Int Symp Auditory Audiological Res,0

2. Batch normalization: Accelerating deep network training by reducing internal covariate shift;ioffe;Proc Int Conf Mach Learn,0

3. A computational model of human auditory signal processing and perception

4. A Fully Convolutional Neural Network for Speech Enhancement

5. DHASP: Differentiable Hearing Aid Speech Processing

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