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 Experiment Videos

On the source-identification method

W M Hartmann1, B Rakerd, J B Gaalaas

  • 1Michigan State University, East Lansing 48824, USA.

The Journal of the Acoustical Society of America
|December 19, 1998
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

A Procedure for Obtaining Initial Values of Parameters in the RAM Model.

Multivariate behavioral research·2016
Same author

Effect of laryngoplasty on respiratory noise reduction in horses with laryngeal hemiplegia.

Equine veterinary journal·2004
Same author

Ventriculocordectomy reduces respiratory noise in horses with laryngeal hemiplegia.

Equine veterinary journal·2003
Same author

Paired-comparison hearing aid preferences: evaluation of an unforced-choice paradigm.

Journal of the American Academy of Audiology·2001
Same author

Binaural coherence edge pitch.

The Journal of the Acoustical Society of America·2001
Same author

Loudness discrimination of speech signals spectrally shaped by a simulated hearing aid.

Journal of speech, language, and hearing research : JSLHR·1999
Same journal

High-resolution depth estimation for multiple wideband sources in deep sea via sparse Bayesian learninga).

The Journal of the Acoustical Society of America·2026
Same journal

Depression markers in speech: An approach based on tract variables dynamics.

The Journal of the Acoustical Society of America·2026
Same journal

The oyster toadfish (Opsanus tau) alters active and diurnal calling amid vessel noise in New York City.

The Journal of the Acoustical Society of America·2026
Same journal

Experimental noise characterisation of phase-locked tandem-rotor in edgewise flight.

The Journal of the Acoustical Society of America·2026
Same journal

The tune-text-temporal synergy: Prosodic effects of final segmental weakening in Neapolitan.

The Journal of the Acoustical Society of America·2026
Same journal

Monitoring vessel movement above critical offshore infrastructure using distributed acoustic sensing.

The Journal of the Acoustical Society of America·2026
See all related articles

This study models sound source identification, a psychophysical method for sound localization. The findings offer guidelines for designing and analyzing experiments on auditory perception and localization.

Area of Science:

  • Auditory perception
  • Psychophysics
  • Acoustic analysis

Background:

  • The source identification method is a standard psychophysical procedure.
  • Listener localization ability can be modeled using internal response distributions (width and bias).

Purpose of the Study:

  • To theoretically investigate the source identification method.
  • To explore relationships between experimental observables (error, variability) and internal distribution parameters.
  • To compare theoretical predictions with experimental data, especially concerning the number of sound sources.

Main Methods:

  • Statistical modeling of listener responses.
  • Theoretical analysis of the relationships between observables and model parameters.
  • Testing the model against empirical source-identification experiments.

Related Experiment Videos

Main Results:

  • The statistical model accurately accounts for experimental data, including easy and difficult conditions.
  • The model successfully predicts the dependence of observable statistics on the number of sources.
  • Key relationships between experimental error, variability, and internal distribution parameters were elucidated.

Conclusions:

  • The developed statistical model provides a robust framework for understanding sound source identification.
  • The findings offer practical guidelines for designing and analyzing auditory localization experiments.
  • This research advances the understanding of human auditory perception and spatial hearing.