AIMC Topic: Hearing Loss
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Sixty Years of Frequency-Domain Monaural Speech Enhancement: From Traditional to Deep Learning Methods.
Trends in hearing
Jan 1, 2023
Frequency-domain monaural speech enhancement has been extensively studied for over 60 years, and a great number of methods have been proposed and applied to many devices. In the last decade, monaural speech enhancement has made tremendous progress wi...
Deep learning based speaker separation and dereverberation can generalize across different languages to improve intelligibility.
The Journal of the Acoustical Society of America
Oct 1, 2021
The practical efficacy of deep learning based speaker separation and/or dereverberation hinges on its ability to generalize to conditions not employed during neural network training. The current study was designed to assess the ability to generalize ...
An effectively causal deep learning algorithm to increase intelligibility in untrained noises for hearing-impaired listeners.
The Journal of the Acoustical Society of America
Jun 1, 2021
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 ...
Perceptual Effects of Adjusting Hearing-Aid Gain by Means of a Machine-Learning Approach Based on Individual User Preference.
Trends in hearing
Jan 1, 2019
This study investigated a method to adjust hearing-aid gain by use of a machine-learning algorithm that estimates the optimal setting of gain parameters based on user preference indicated in an iterative paired-comparison procedure. Twenty hearing-im...
Online Machine Learning Audiometry.
Ear and hearing
Jan 1, 2019
OBJECTIVES: A confluence of recent developments in cloud computing, real-time web audio and machine learning psychometric function estimation has made wide dissemination of sophisticated turn-key audiometric assessments possible. The authors have com...
Use of a Deep Recurrent Neural Network to Reduce Wind Noise: Effects on Judged Speech Intelligibility and Sound Quality.
Trends in hearing
Jan 1, 2018
Despite great advances in hearing-aid technology, users still experience problems with noise in windy environments. The potential benefits of using a deep recurrent neural network (RNN) for reducing wind noise were assessed. The RNN was trained using...
Auditory inspired machine learning techniques can improve speech intelligibility and quality for hearing-impaired listeners.
The Journal of the Acoustical Society of America
Mar 1, 2017
Machine-learning based approaches to speech enhancement have recently shown great promise for improving speech intelligibility for hearing-impaired listeners. Here, the performance of three machine-learning algorithms and one classical algorithm, Wie...
Humans
Neural Networks, Computer
Machine Learning
Female
Aged
Hearing Aids
Hearing Loss
Persons with Hearing Disabilities
Speech Perception
Recognition, Psychology
Signal Processing, Computer-Assisted
Audiometry, Speech
Acoustic Stimulation
Perceptual Masking
Electric Stimulation
Male
Speech Intelligibility
Middle Aged
Noise
Difficulty understanding speech in noise by the hearing impaired: underlying causes and technological solutions.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Aug 1, 2016
A primary complaint of hearing-impaired individuals involves poor speech understanding when background noise is present. Hearing aids and cochlear implants often allow good speech understanding in quiet backgrounds. But hearing-impaired individuals a...
[Application of the mathematical model for prognosis in the rehabilitation of children after cochlear implantation].
Vestnik otorinolaringologii
Jan 1, 2016
UNLABELLED: Despite the variety of etiological factors, cochlear implantation (CI) remains the only effective method for the rehabilitation of the patients presenting with total deafness. The aim of this study was the enhancement of the efficiency of...
Fast, Continuous Audiogram Estimation Using Machine Learning.
Ear and hearing
Jan 1, 2015
OBJECTIVES: Pure-tone audiometry has been a staple of hearing assessments for decades. Many different procedures have been proposed for measuring thresholds with pure tones by systematically manipulating intensity one frequency at a time until a disc...
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