Literature DB >> 35855497

Helping People Hear Better with "Smart" Hearing Devices.

Tobias Goehring1, Jessica Monaghan2.   

Abstract

Millions of people around the world have difficulty hearing. Hearing aids and cochlear implants help people hear better, especially in quiet places. Unfortunately, these devices do not always help in noisy situations like busy classrooms or restaurants. This means that a person with hearing loss may struggle to follow a conversation with friends or family and may avoid going out. We used methods from the field of artificial intelligence to develop "smart" hearing aids and cochlear implants that can get rid of background noise. We play many different sounds into a computer program, which learns to pick out the speech sounds and filter out unwanted background noises. Once the computer program has been trained, it is then tested on new examples of noisy speech and can be incorporated into hearing aids or cochlear implants. These "smart" approaches can help people with hearing loss understand speech better in noisy situations.

Entities:  

Year:  2022        PMID: 35855497      PMCID: PMC7613069     

Source DB:  PubMed          Journal:  Front Young Minds        ISSN: 2296-6846


  5 in total

1.  Deep Learning Reinvents the Hearing Aid: Finally, wearers of hearing aids can pick out a voice in a crowded room.

Authors:  DeLiang Wang
Journal:  IEEE Spectr       Date:  2017-02-28       Impact factor: 2.875

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

Authors:  Jessica J M Monaghan; Tobias Goehring; Xin Yang; Federico Bolner; Shangqiguo Wang; Matthew C M Wright; Stefan Bleeck
Journal:  J Acoust Soc Am       Date:  2017-03       Impact factor: 1.840

3.  Environment-specific noise suppression for improved speech intelligibility by cochlear implant users.

Authors:  Yi Hu; Philipos C Loizou
Journal:  J Acoust Soc Am       Date:  2010-06       Impact factor: 1.840

4.  Speech enhancement based on neural networks improves speech intelligibility in noise for cochlear implant users.

Authors:  Tobias Goehring; Federico Bolner; Jessica J M Monaghan; Bas van Dijk; Andrzej Zarowski; Stefan Bleeck
Journal:  Hear Res       Date:  2016-11-30       Impact factor: 3.208

5.  Using recurrent neural networks to improve the perception of speech in non-stationary noise by people with cochlear implants.

Authors:  Tobias Goehring; Mahmoud Keshavarzi; Robert P Carlyon; Brian C J Moore
Journal:  J Acoust Soc Am       Date:  2019-07       Impact factor: 1.840

  5 in total

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