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

Dimensional Analysis02:19

Dimensional Analysis

22.3K
The concept of dimension is important because every mathematical equation linking physical quantities must be dimensionally consistent, implying that mathematical equations must meet the following two rules. The first rule is that, in an equation, the expressions on each side of the equal sign must have the same dimensions. This is fairly intuitive since we can only add or subtract quantities of the same type (dimension). The second rule states that, in an equation, the arguments of any of the...
22.3K
Dimensional Analysis01:23

Dimensional Analysis

1.9K
Dimensional analysis is a powerful tool that is used in physics and engineering to understand and predict the behavior of physical systems. The basic idea behind dimensional analysis is to express physical quantities in terms of fundamental dimensions such as the mass, length, and time. Derived dimensions like the velocity, acceleration, and force are derived from the combinations of these fundamental dimensions.
Dimensional analysis allows us to analyze and compare physical quantities on a...
1.9K
Dimensional Analysis03:40

Dimensional Analysis

58.4K
Dimensional analysis, also known as the factor label method, is a versatile approach for mathematical operations. The main principle behind this approach is: the units of quantities must be subjected to the same mathematical operations as their associated numbers. This method can be applied to computations ranging from simple unit conversions to more complex and multi-step calculations involving several different quantities and their units.
Conversion Factors and Dimensional Analysis
The unit...
58.4K
Dimensional Analysis01:27

Dimensional Analysis

584
Dimensional analysis is a valuable technique in fluid mechanics for simplifying complex problems by reducing them into dimensionless groups. These groups capture the essential relationships between the variables involved, allowing researchers and engineers to analyze fluid flow without dealing with each variable individually. This approach reduces the number of independent variables, allowing for easier analysis and better understanding of physical phenomena.
In fluid mechanics, dimensional...
584
Generalization, Discrimination, and Extinction01:24

Generalization, Discrimination, and Extinction

1.3K
Generalization, discrimination, and extinction are key concepts in operant conditioning that influence how behaviors are learned and maintained.
Generalization occurs when a behavior reinforced in one context is performed in similar situations. For instance, a student who studies diligently for calculus and receives excellent grades might apply the same study habits to psychology and history, expecting similar results. Generalization shows how learning in one setting can influence behavior in...
1.3K
Problem Solving: Dimensional Analysis01:08

Problem Solving: Dimensional Analysis

5.7K
Every mathematical equation that connects separate distinct physical quantities must be dimensionally consistent, which implies it must abide by two rules. For this reason, the concept of dimension is crucial. The first rule is that an equation's expressions on either side of an equality must have the exact same dimension, i.e., quantities of the same dimension can be added or removed. The second rule stipulates that all popular mathematical functions, such as exponential, logarithmic, and...
5.7K

You might also read

Related Articles

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

Sort by
Same author

Transfer of statistical learning from speech perception to production generalizes to reading.

Psychonomic bulletin & review·2026
Same author

Speech motor control is not sequestered from general auditory processes.

Journal of experimental psychology. General·2026
Same author

Exposure to an accent transfers to speech production in a single shot.

Cognition·2025
Same author

Accented speech modulates multiple event-related potential components across multiple levels of language processing.

Communications psychology·2025
Same author

Speech Perception is Speech Learning.

Current directions in psychological science·2025
Same author

Statistical learning dynamically shapes auditory perception.

NPJ science of learning·2025
Same journal

Low prevalence targets are primarily missed due to mind wandering.

Attention, perception & psychophysics·2026
Same journal

An introduction to the special issue celebrating Mary A. Peterson.

Attention, perception & psychophysics·2026
Same journal

Properties of the threshold stimulus exposure duration (TSED) measure of visual search efficiency.

Attention, perception & psychophysics·2026
Same journal

Auditory selective attention in depth: Investigating directional dependency across front, lateral, and rear spaces.

Attention, perception & psychophysics·2026
Same journal

Dissociations between stereoacuity and visual acuity with binocular night vision goggles.

Attention, perception & psychophysics·2026
Same journal

Reward-based prioritization and perceptual feature effects on attentional flexibility in working memory.

Attention, perception & psychophysics·2026
See all related articles

Related Experiment Video

Updated: Dec 31, 2025

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.9K

Generalization of dimension-based statistical learning.

Kaori Idemaru1, Lori L Holt2

  • 1Department of East Asian Languages and Literatures, University of Oregon, Eugene, OR, 97403, USA. idemaru@uoregon.edu.

Attention, Perception & Psychophysics
|January 8, 2020
PubMed
Summary
This summary is machine-generated.

Statistical learning shapes how we perceive speech sounds like [b] and [p]. Learning adapts to new sound patterns, but generalization is weaker in unfamiliar contexts, supporting context-dependent speech perception.

Keywords:
Cue weightingDimension-based learningGeneralizationSpeech perceptionStatistical learning

More Related Videos

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
08:05

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

8.0K
An Operant Intra-/Extra-dimensional Set-shift Task for Mice
08:35

An Operant Intra-/Extra-dimensional Set-shift Task for Mice

Published on: January 22, 2016

12.6K

Related Experiment Videos

Last Updated: Dec 31, 2025

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.9K
Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
08:05

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

8.0K
An Operant Intra-/Extra-dimensional Set-shift Task for Mice
08:35

An Operant Intra-/Extra-dimensional Set-shift Task for Mice

Published on: January 22, 2016

12.6K

Area of Science:

  • Psycholinguistics
  • Speech Perception
  • Auditory Learning

Background:

  • The relationship between acoustic properties and speech sound categories is dynamic.
  • Statistical learning influences how individuals adapt to variations in speech sounds over time.

Purpose of the Study:

  • To investigate perceptual statistical learning of accented [b] and [p] speech categories.
  • To examine the generalization of this learning across different contexts and its sensitivity to the learning environment.

Main Methods:

  • Three studies utilized online word recognition tasks.
  • Participants learned artificially accented [b] and [p] speech categories.
  • Generalization of learning was tested across contexts and with varied word list sizes.

Main Results:

  • Learning of accented [b] and [p] speech categories generalized across experienced contexts.
  • Generalization was weaker in contexts not encountered during the learning phase.
  • This effect persisted even with the same speaker and speech categories.

Conclusions:

  • Speech perception is supported by a robust model sensitive to context-specific acoustic-phonetic mappings.
  • Perceptual learning of speech categories is influenced by the statistical regularities experienced.
  • Context-dependent variations significantly impact the generalization of learned speech patterns.