Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Hearing01:31

Hearing

54.1K
When we hear a sound, our nervous system is detecting sound waves—pressure waves of mechanical energy traveling through a medium. The frequency of the wave is perceived as pitch, while the amplitude is perceived as loudness.
54.1K
Auditory Perception01:17

Auditory Perception

669
The auditory system is essential for sound perception, utilizing various critical structures. When sound waves enter the outer ear, they travel through the ear canal and cause the eardrum to vibrate. These vibrations are then transmitted to the middle ear, where three tiny bones – the malleus, incus, and stapes – amplify the sound. This amplification is crucial, as it ensures that the sound vibrations are strong enough to be conveyed to the inner ear. These vibrations then reach the...
669
Perceiving Loudness, Pitch, and Location01:21

Perceiving Loudness, Pitch, and Location

546
The human brain perceives pitch through two primary mechanisms reflected in place theory and frequency theory. Each mechanism describes how sound waves are interpreted as specific pitches by the brain, offering insights into the intricate processes of auditory perception.
Place theory, or place coding, suggests that different pitches are heard because various sound waves activate specific locations along the cochlea's basilar membrane. The brain determines the pitch of a sound by...
546
Auditory Pathway01:15

Auditory Pathway

6.0K
Auditory pathways constitute the complex neural circuits responsible for transmitting and interpreting auditory information from the peripheral auditory system to the brain. Sound waves are initially captured by the outer ear, funneled through the ear canal, and reach the tympanic membrane (eardrum). These vibrations are transmitted via the middle ear's ossicles to the inner ear's cochlea.
When viewed cross-sectionally, the cochlea reveals the scala vestibuli and scala tympani flanking...
6.0K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Perceptual Effects of Adjusting Hearing-Aid Gain by Means of a Machine-Learning Approach Based on Individual User Preference.

Trends in hearing·2019
Same author

Investigating lexical competition and the cost of phonemic restoration.

The Journal of the Acoustical Society of America·2018
Same author

Effects of Surprisal and Locality on Danish Sentence Processing: An Eye-Tracking Investigation.

Journal of psycholinguistic research·2017
Same author

Cognitive Load in Voice Therapy Carry-Over Exercises.

Journal of speech, language, and hearing research : JSLHR·2016
Same author

Givenness, complexity, and the Danish dative alternation.

Memory & cognition·2013
Same author

Probability and surprisal in auditory comprehension of morphologically complex words.

Cognition·2012

Related Experiment Video

Updated: Oct 18, 2025

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages
06:04

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages

Published on: March 24, 2023

521

The Collaboration between Hearing Aid Users and Artificial Intelligence to Optimize Sound.

Laura Winther Balling1, Lasse Lohilahti Mølgaard2, Oliver Townend1

  • 1Widex, Lynge, Denmark.

Seminars in Hearing
|October 1, 2021
PubMed
Summary

Artificial intelligence (AI) in hearing aids uses Bayesian optimization to adapt to individual users and challenging listening environments. This technology enhances hearing care by collecting valuable user data for future development.

Keywords:
artificial intelligencedata-driven hearing carehearing aid classificationlistening intention

More Related Videos

Sound Source Localization Testing in Single-sided Deafness Following Bone Conduction Intervention
04:32

Sound Source Localization Testing in Single-sided Deafness Following Bone Conduction Intervention

Published on: December 20, 2024

527
Author Spotlight: Optimizing EAS with Long Electrodes for Enhanced Cochlear Coverage and Hearing Preservation
03:49

Author Spotlight: Optimizing EAS with Long Electrodes for Enhanced Cochlear Coverage and Hearing Preservation

Published on: October 11, 2024

983

Related Experiment Videos

Last Updated: Oct 18, 2025

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages
06:04

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages

Published on: March 24, 2023

521
Sound Source Localization Testing in Single-sided Deafness Following Bone Conduction Intervention
04:32

Sound Source Localization Testing in Single-sided Deafness Following Bone Conduction Intervention

Published on: December 20, 2024

527
Author Spotlight: Optimizing EAS with Long Electrodes for Enhanced Cochlear Coverage and Hearing Preservation
03:49

Author Spotlight: Optimizing EAS with Long Electrodes for Enhanced Cochlear Coverage and Hearing Preservation

Published on: October 11, 2024

983

Area of Science:

  • Audiology
  • Artificial Intelligence
  • Machine Learning

Background:

  • Hearing aid performance relies on average user and environment assumptions.
  • Deviations from these assumptions can lead to suboptimal hearing aid function.
  • Individualized hearing needs are not always met by traditional settings.

Purpose of the Study:

  • To introduce an artificial intelligence (AI) mechanism for adaptive hearing aid gain and signal processing.
  • To demonstrate how Bayesian optimization can personalize hearing aid performance.
  • To highlight the data generation capabilities of AI for hearing science.

Main Methods:

  • Utilizing a continuous AI mechanism with Bayesian optimization.
  • Collecting user input and environmental data.
  • Summarizing laboratory and field study results.

Main Results:

  • AI mechanism effectively addresses individual user differences and challenging environments.
  • Generated user data provides insights into diverse listening situations.
  • Studies confirm AI's efficacy in both controlled and real-world settings.

Conclusions:

  • AI-driven hearing aids offer personalized solutions beyond average assumptions.
  • User data generated by AI is crucial for advancing hearing aid technology and audiological understanding.
  • AI facilitates a deeper scientific understanding of challenging listening environments and user needs.