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Audiometry, Speech

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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...