AIMC Topic: Hearing

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A model of speech recognition for hearing-impaired listeners based on deep learning.

The Journal of the Acoustical Society of America Mar 1, 2022
Automatic speech recognition (ASR) has made major progress based on deep machine learning, which motivated the use of deep neural networks (DNNs) as perception models and specifically to predict human speech recognition (HSR). This study investigates...
Humans Deep Learning Speech Perception Presbycusis Speech Hearing
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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 ...
Speech Perception Hearing Loss, Sensorineural Hearing Speech Intelligibility Algorithms Hearing Aids Deep Learning Hearing Loss Humans
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[Preliminary application of robot-assisted electrode insertion in cochlear implantation].

Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery Oct 7, 2020
To evaluate the safety and outcomes of robot-assisted electrode insertion in cochlear implantation. We first reported the case of robot-assisted electrode insertion of cochlear implantation in October 2019. A new slim electrode array of Nurotron co...
Robotics Cochlear Implantation Adult Cochlea Electrodes, Implanted Hearing Cochlear Implants Humans
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A talker-independent deep learning algorithm to increase intelligibility for hearing-impaired listeners in reverberant competing talker conditions.

The Journal of the Acoustical Society of America Jun 1, 2020
Deep learning based speech separation or noise reduction needs to generalize to voices not encountered during training and to operate under multiple corruptions. The current study provides such a demonstration for hearing-impaired (HI) listeners. Sen...
Deep Learning Humans Speech Intelligibility Hearing Speech Perception Hearing Loss, Sensorineural Algorithms
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A Comparative Study of Features for Acoustic Cough Detection Using Deep Architectures.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Automatic cough detection is key to tracking the condition of patients suffering from tuberculosis. We evaluate various acoustic features for performing cough detection using deep architectures. As most previous studies have adopted features designed...
Tuberculosis Acoustics Speech Hearing Humans Cough Neural Networks, Computer
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An algorithm to increase intelligibility for hearing-impaired listeners in the presence of a competing talker.

The Journal of the Acoustical Society of America Jun 1, 2017
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...
Hearing Loss, Sensorineural Correction of Hearing Impairment Audiometry, Speech Perceptual Masking Signal-To-Noise Ratio Speech Perception Comprehension Auditory Threshold Persons with Hearing Disabilities Signal Processing, Computer-Assisted Humans Female Young Adult Speech Intelligibility Middle Aged Aged Male Acoustic Stimulation Hearing Aids Deep Learning Hearing
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