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Perceptual Masking

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Statistical learning of parts and wholes: A neural network approach.

Journal of experimental psychology. General
Statistical learning is often considered to be a means of discovering the units of perception, such as words and objects, and representing them as explicit "chunks." However, entities are not undifferentiated wholes but often contain parts that contr...

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...

An algorithm to increase intelligibility for hearing-impaired listeners in the presence of a competing talker.

The Journal of the Acoustical Society of America
Individuals with hearing impairment have particular difficulty perceptually segregating concurrent voices and understanding a talker in the presence of a competing voice. In contrast, individuals with normal hearing perform this task quite well. This...

Single-ended prediction of listening effort using deep neural networks.

Hearing research
The effort required to listen to and understand noisy speech is an important factor in the evaluation of noise reduction schemes. This paper introduces a model for Listening Effort prediction from Acoustic Parameters (LEAP). The model is based on met...

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...

Deep learning based speaker separation and dereverberation can generalize across different languages to improve intelligibility.

The Journal of the Acoustical Society of America
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 ...

Using deep learning to improve the intelligibility of a target speaker in noisy multi-talker environments for people with normal hearing and hearing loss.

The Journal of the Acoustical Society of America
Understanding speech in noisy environments is a challenging task, especially in communication situations with several competing speakers. Despite their ongoing improvement, assistive listening devices and speech processing approaches still do not per...

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...