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

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.
Sound Intensity Level00:53

Sound Intensity Level

Humans perceive sound by hearing. The human ear helps sound waves reach the brain, which then interprets the waves and creates the perception of hearing. The loudness of the environment in which a person is located determines whether they can distinguish between different sound sources.
The human ear can perceive an extensive range of sound intensity, necessitating the use of the logarithmic scale to define a physical quantity—the intensity level. It is a ratio of two intensities and hence a...
Perceiving Loudness, Pitch, and Location01:21

Perceiving Loudness, Pitch, and Location

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 identifying...
Perception of Sound Waves01:01

Perception of Sound Waves

The human ear is not equally sensitive to all frequencies in the audible range. It may perceive sound waves with the same pressure but different frequencies as having different loudness. Moreover, the perception of sound waves depends on the health of an individual's ears, which decays with age. The health of one's ears may also be affected by regular exposure to loud noises.
The pitch of a sound depends on the frequency and the pressure amplitude of the source. Two sounds of the same frequency...
Echo01:06

Echo

The human ear cannot distinguish between two sources of sound if they happen to reach within a specific time interval, typically 0.1 seconds apart. More than this, and they are perceived as separate sources.
Imagine the sound is reflected back to the ears. Assuming that the source is very close to the human, the difference between hearing the two sounds—the emitted sound and the reflected sound—may be more than the minimum time for perceiving distinct sounds. If this is the case, then the...
Classification of Signals01:30

Classification of Signals

In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...

You might also read

Related Articles

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

Sort by
Same author

Unusual neuroimaging in superficial siderosis.

Neurology·2005
Same author

Tuberculin survey in government high school of Dharan municipality.

JNMA; journal of the Nepal Medical Association·2005
Same author

Prediction of fixation failure after sliding hip screw fixation [Injury 2004;35:994-8].

Injury·2005
Same author

The incidence of visual impairment due to diabetic retinopathy in Leeds.

Eye (London, England)·2005
Same author

Structural characterization, expression analysis and evolution of the red/far-red sensing photoreceptor gene, phytochrome C (PHYC), localized on the 'B' genome of hexaploid wheat (Triticum aestivum L.).

Planta·2005
Same author

Neurologic manifestations in welders with pallidal MRI T1 hyperintensity.

Neurology·2005
Same journal

Harmonic memory in phasor neural networks.

Biological cybernetics·2026
Same journal

Correction: Decreased spinal inhibition leads to undiversified locomotor patterns.

Biological cybernetics·2026
Same journal

Foundational issues of network models in biology.

Biological cybernetics·2026
Same journal

Dynamical mechanisms for coordinating long-term working memory based on the precision of spike-timing in cortical neurons.

Biological cybernetics·2026
Same journal

Distinct dopaminergic spike-timing-dependent plasticity rules are suited to different functional roles.

Biological cybernetics·2026
Same journal

Fluctuation-response relations for a two-stage population of spiking neurons stimulated by common noise.

Biological cybernetics·2026
See all related articles

Related Experiment Video

Updated: Jun 25, 2026

Flying Insect Detection and Classification with Inexpensive Sensors
05:16

Flying Insect Detection and Classification with Inexpensive Sensors

Published on: October 15, 2014

Categorization of environmental sounds.

R K Reddy1, V Ramachandra, N Kumar

  • 1National Brain Research Centre, Manesar, Haryana, India.

Biological Cybernetics
|March 5, 2009
PubMed
Summary
This summary is machine-generated.

Environmental sounds are non-stationary. We developed measures to analyze spectral dynamics, categorizing sounds as simple (slow dynamics) or complex (rapid dynamics), suggesting this as a new classification scheme.

More Related Videos

Experience is Instrumental in Tuning a Link Between Language and Cognition: Evidence from 6- to 7- Month-Old Infants' Object Categorization
05:35

Experience is Instrumental in Tuning a Link Between Language and Cognition: Evidence from 6- to 7- Month-Old Infants' Object Categorization

Published on: April 19, 2017

An Automated System for Sound Localization Testing in Hearing-Impaired Listeners
07:52

An Automated System for Sound Localization Testing in Hearing-Impaired Listeners

Published on: March 13, 2026

Related Experiment Videos

Last Updated: Jun 25, 2026

Flying Insect Detection and Classification with Inexpensive Sensors
05:16

Flying Insect Detection and Classification with Inexpensive Sensors

Published on: October 15, 2014

Experience is Instrumental in Tuning a Link Between Language and Cognition: Evidence from 6- to 7- Month-Old Infants' Object Categorization
05:35

Experience is Instrumental in Tuning a Link Between Language and Cognition: Evidence from 6- to 7- Month-Old Infants' Object Categorization

Published on: April 19, 2017

An Automated System for Sound Localization Testing in Hearing-Impaired Listeners
07:52

An Automated System for Sound Localization Testing in Hearing-Impaired Listeners

Published on: March 13, 2026

Area of Science:

  • Acoustics and Auditory Neuroscience

Background:

  • Environmental sounds exhibit time-dependent spectral dynamics, a characteristic known as non-stationarity.
  • Understanding these dynamics is crucial for environmental sound analysis and auditory perception research.

Purpose of the Study:

  • To develop quantitative measures for analyzing the spectral dynamics of environmental sound signals.
  • To establish a novel categorization scheme for environmental sounds based on their spectral dynamics.

Main Methods:

  • Development of novel analytical measures to quantify spectral dynamics in environmental sound signals.
  • Classification of sound signals based on the rate of change in their spectral characteristics.

Main Results:

  • Environmental sounds were successfully categorized into two distinct groups: simple sounds with slow spectral dynamics and complex sounds with rapid spectral dynamics.
  • The rate of spectral dynamics emerged as a significant differentiating factor between sound categories.

Conclusions:

  • The rate of spectral dynamics provides a viable metric for classifying environmental sound signals.
  • This approach offers a new perspective for organizing and understanding the complexity of natural auditory scenes.