Authors: Peter Leer, Jesper Jensen, Laurel Carney, Zheng-Hua Tan, Jan Østergaard, Lars Bramsløw

Published on: March 15, 2024

Impact Score: 7.4

Arxiv code: Arxiv:2403.10420

Summary

• What is new: Introduction of a DNN-based approach for hearing-loss compensation trained on auditory models.
• Why this is important: Conventional hearing aids fall short in providing satisfactory compensation for hearing loss.
• What the research proposes: A DNN-based approach trained on the outputs of auditory models responding to speech signals.
• Results: Increased speech intelligibility and superior perceived speech quality compared to conventional methods.

Technical Details

Technological frameworks used: Deep Neural Networks (DNNs)

Models used: Auditory-nerve model

Data used: Outputs from hearing-impaired and normal-hearing DNN-based auditory models in response to speech signals

Potential Impact

Hearing aid manufacturers, health tech companies specializing in auditory devices

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