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

Multiresolution spectrotemporal analysis of complex sounds.

Taishih Chi1, Powen Ru, Shihab A Shamma

  • 1Center for Auditory and Acoustics Research, Institute for Systems Research Electrical and Computer Engineering Department, University of Maryland, College Park, Maryland 20742, USA.

The Journal of the Acoustical Society of America
|September 15, 2005
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

Similar Response Dynamics Represent Opposite Behaviors and Rewards in the Frontal Cortex.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2026
Same author

Similar Dynamic Frontal Cortex Representations of Auditory Stimuli Cueing Opposite Actions and Rewards.

bioRxiv : the preprint server for biology·2025
Same author

Performance on stochastic figure-ground perception varies with individual differences in speech-in-noise recognition and working memory capacity.

The Journal of the Acoustical Society of America·2023
Same author

Accurate Decoding of Imagined and Heard Melodies.

Frontiers in neuroscience·2021
Same author

The Music of Silence: Part II: Music Listening Induces Imagery Responses.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2021
Same author

The Music of Silence: Part I: Responses to Musical Imagery Encode Melodic Expectations and Acoustics.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2021
Same journal

Sibilant differentiation before and after tongue cancer surgery: Acoustics, kinematics and the role of sensorimotor controla).

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

BioNet-A: Ultrasonic echo representation network for target discrimination using active SONAR.

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

Empty soft-drink cans and mass-loaded rods: Analogous homework problems from acoustic and mechanical domains.

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

Erratum: Statistical wave field theory: Anisotropic wave fields under Neumann's boundary condition [J. Acoust. Soc. Am. 159(3), 2265-2280 (2026)].

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

On the modification of tip leakage noise sources by porous treatment.

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

An educational opportunity: Acoustics in an empty room.

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

This study presents a computational model for auditory analysis, capturing key spectral and temporal sound features. This model aids in understanding speech intelligibility and auditory perception.

Area of Science:

  • Computational Auditory Neuroscience
  • Psychoacoustics
  • Signal Processing

Background:

  • Auditory system processing involves complex spectral and temporal feature extraction.
  • Existing models offer insights but lack a unified framework for early and central auditory stages.
  • Psychoacoustical and neurophysiological data inform computational models of hearing.

Purpose of the Study:

  • To present a comprehensive mathematical formulation of a computational auditory analysis model.
  • To unify spectral and temporal feature representation in auditory processing.
  • To evaluate the model's fidelity and the contribution of different features to sound perception.

Main Methods:

  • Developing a multiresolution computational model inspired by auditory system findings.

Related Experiment Videos

  • Applying mathematical formulations to describe signal transformation through model stages.
  • Utilizing sound reconstruction algorithms to analyze model output.

    • Main Results:

    • The model provides a unified representation of spectral and temporal auditory features.
    • Previous versions have successfully assessed speech intelligibility and phase sensitivity.
    • The mathematical formulation clarifies signal processing within the model.

    Conclusions:

    • The computational model offers a robust framework for auditory analysis.
    • It integrates psychoacoustical and neurophysiological insights into a cohesive auditory processing model.
    • Further research can explore feature contributions to sound perception using reconstruction algorithms.