AIP Publishing LLC
AIP Publishing LLC
  • pubs.aip.org
  • AIP
  • AIP China
  • University Science Books
  • Resources
    • Researchers
    • Librarians
    • Publishing Partners
    • Topical Portfolios
    • Commercial Partners
  • Publications

    Find the Right Journal

    Explore the AIP Publishing collection by title, topic, impact, citations, and more.
    Browse Journals

    Latest Content

    Read about the newest discoveries and developments in the physical sciences.
    See What's New

    Publications

    • Journals
    • Books
    • Physics Today
    • AIP Conference Proceedings
    • Scilight
    • Find the Right Journal
    • Latest Content
  • About
    • About Us
    • News and Announcements
    • Careers
    • Events
    • Leadership
    • Contact
  • pubs.aip.org
  • AIP
  • AIP China
  • University Science Books

Machine Learning Improves Human Speech Recognition

  • March 1, 2022
  • The Journal of the Acoustical Society of America
  • News
Share:

From the Journal: The Journal of the Acoustical Society of America

WASHINGTON, March 1, 2022 — Hearing loss is a rapidly growing area of scientific research as the number of baby boomers dealing with hearing loss continues to increase as they age.

To understand how hearing loss impacts people, researchers study people’s ability to recognize speech. It is more difficult for people to recognize human speech if there is reverberation, some hearing impairment, or significant background noise, such as traffic noise or multiple speakers.

Overview of the human speech recognition model CREDIT: Jana Roßbach
Overview of the human speech recognition model CREDIT: Jana Roßbach

As a result, hearing aid algorithms are often used to improve human speech recognition. To evaluate such algorithms, researchers perform experiments that aim to determine the signal-to-noise ratio at which a specific number of words (commonly 50%) are recognized. These tests, however, are time- and cost-intensive.

In The Journal of the Acoustical Society of America, published by the Acoustical Society of America through AIP Publishing, researchers from Germany explore a human speech recognition model based on machine learning and deep neural networks.

“The novelty of our model is that it provides good predictions for hearing-impaired listeners for noise types with very different complexity and shows both low errors and high correlations with the measured data,” said author Jana Roßbach, from Carl Von Ossietzky University.

The researchers calculated how many words per sentence a listener understands using automatic speech recognition (ASR). Most people are familiar with ASR through speech recognition tools like Alexa and Siri.

The study consisted of eight normal-hearing and 20 hearing-impaired listeners who were exposed to a variety of complex noises that mask the speech. The hearing-impaired listeners were categorized into three groups with different levels of age-related hearing loss.

The model allowed the researchers to predict the human speech recognition performance of hearing-impaired listeners with different degrees of hearing loss for a variety of noise maskers with increasing complexity in temporal modulation and similarity to real speech. The possible hearing loss of a person could be considered individually.

“We were most surprised that the predictions worked well for all noise types. We expected the model to have problems when using a single competing talker. However, that was not the case,” said Roßbach.

The model created predictions for single-ear hearing. Going forward, the researchers will develop a binaural model since understanding speech is impacted by two-ear hearing.

In addition to predicting speech intelligibility, the model could also potentially be used to predict listening effort or speech quality as these topics are very related.

###

For more information:
Larry Frum
media@aip.org
301-209-3090

Article Title

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

Authors

Jana Roßbach, Birger Kollmeier and Bernd T. Meyer

Author Affiliations

Carl Von Ossietzky University


The Journal of the Acoustical Society of America

Since 1929, The Journal of the Acoustical Society of America (JASA) has been the leading source of theoretical and experimental research results in the broad interdisciplinary subject of sound.

https://asa.scitation.org/journal/jas

Share:
  • Fish Generate Movable Pairs of Vortices to Propel Them Forward Like Body Waves
  • Cloth Masks Inferior for Protection Against Airborne Viral Spread
Decorative footer image

Keep Up With AIP Publishing

Sign up for the AIP newsletter to receive the latest news and information from AIP Publishing.
Sign Up
AIP Publishing and the Purpose Led Publishing logos

AIP PUBLISHING

1305 Walt Whitman Road,
Suite 110
Melville, NY 11747
(516) 576-2200

Resources

  • Researchers
  • Librarians
  • Publishing Partners
  • Commercial Partners

About

  • About Us
  • Careers 
  • Leadership

Support

  • Contact Us
  • Terms Of Use
  • Privacy Policy

© 2025 AIP Publishing LLC