AIMC Topic: Hearing Aids

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Speech signal enhancement in cocktail party scenarios by deep learning based virtual sensing of head-mounted microphones.

Hearing research
The cocktail party effect refers to the human sense of hearing's ability to pay attention to a single conversation while filtering out all other background noise. To mimic this human hearing ability for people with hearing loss, scientists integrate ...

Environmental Noise Classification Using Convolutional Neural Networks with Input Transform for Hearing Aids.

International journal of environmental research and public health
Hearing aids are essential for people with hearing loss, and noise estimation and classification are some of the most important technologies used in devices. This paper presents an environmental noise classification algorithm for hearing aids that us...

Cascade recurring deep networks for audible range prediction.

BMC medical informatics and decision making
BACKGROUND: Hearing Aids amplify sounds at certain frequencies to help patients, who have hearing loss, to improve the quality of life. Variables affecting hearing improvement include the characteristics of the patients' hearing loss, the characteris...

Software intelligent system for effective solutions for hearing impaired subjects.

International journal of medical informatics
PURPOSE: The anatomy and physiology of the ear is complex in nature, which makes it a challenge for audiologists to prescribe solutions for varied hearing-impaired subjects. There is a need to increase the satisfaction level of hearing-aid users by a...

Piezoelectric nanofiber-based intelligent hearing system.

Science advances
Hearing loss, affecting individuals of all ages, can impair education, social function, and quality of life. Current treatments, such as hearing aids and implants, aim to mitigate these effects but often fall short in addressing the critical issue of...

Neural-WDRC: A Deep Learning Wide Dynamic Range Compression Method Combined With Controllable Noise Reduction for Hearing Aids.

Trends in hearing
Wide dynamic range compression (WDRC) and noise reduction both play important roles in hearing aids. WDRC provides level-dependent amplification so that the level of sound produced by the hearing aid falls between the hearing threshold and the highes...

Tissue Classification After Bone-Anchored Hearing Implant Surgery: A Machine Learning Approach to Monitoring Skin Response.

Otology & neurotology : official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology
HYPOTHESIS: Here, we aim to 1) expand the available evidence for the use of machine learning techniques for soft tissue classification after BCD surgery and 2) discuss the implications of such approaches toward the development of classification appli...

Progress made in the efficacy and viability of deep-learning-based noise reduction.

The Journal of the Acoustical Society of America
Recent years have brought considerable advances to our ability to increase intelligibility through deep-learning-based noise reduction, especially for hearing-impaired (HI) listeners. In this study, intelligibility improvements resulting from a curre...

A deep learning solution to the marginal stability problems of acoustic feedback systems for hearing aids.

The Journal of the Acoustical Society of America
For hearing aids, it is critical to reduce the acoustic coupling between the receiver and microphone to ensure that prescribed gains are below the maximum stable gain, thus preventing acoustic feedback. Methods for doing this include fixed and adapti...

An effectively causal deep learning algorithm to increase intelligibility in untrained noises for hearing-impaired listeners.

The Journal of the Acoustical Society of America
Real-time operation is critical for noise reduction in hearing technology. The essential requirement of real-time operation is causality-that an algorithm does not use future time-frame information and, instead, completes its operation by the end of ...