AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Noise

Showing 121 to 128 of 128 articles

Clear Filters

Perceptual Effects of Adjusting Hearing-Aid Gain by Means of a Machine-Learning Approach Based on Individual User Preference.

Trends in hearing
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...

A deep learning based segregation algorithm to increase speech intelligibility for hearing-impaired listeners in reverberant-noisy conditions.

The Journal of the Acoustical Society of America
Recently, deep learning based speech segregation has been shown to improve human speech intelligibility in noisy environments. However, one important factor not yet considered is room reverberation, which characterizes typical daily environments. The...

Use of a Deep Recurrent Neural Network to Reduce Wind Noise: Effects on Judged Speech Intelligibility and Sound Quality.

Trends in hearing
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...

Deep Learning-Based Noise Reduction Approach to Improve Speech Intelligibility for Cochlear Implant Recipients.

Ear and hearing
OBJECTIVE: We investigate the clinical effectiveness of a novel deep learning-based noise reduction (NR) approach under noisy conditions with challenging noise types at low signal to noise ratio (SNR) levels for Mandarin-speaking cochlear implant (CI...

Auditory inspired machine learning techniques can improve speech intelligibility and quality for hearing-impaired listeners.

The Journal of the Acoustical Society of America
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...

Smartphone-Based System for Learning and Inferring Hearing Aid Settings.

Journal of the American Academy of Audiology
BACKGROUND: Previous research has shown that hearing aid wearers can successfully self-train their instruments' gain-frequency response and compression parameters in everyday situations. Combining hearing aids with a smartphone introduces additional ...

Improving quality and intelligibility of speech using single microphone for the broadband fMRI noise at low SNR.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Functional Magnetic Resonance Imaging (fMRI) is used in many diagnostic procedures for neurological related disorders. Strong broadband acoustic noise generated during fMRI scan interferes with the speech communication between the physician and the p...

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
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...