Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Perception of Sound Waves01:01

Perception of Sound Waves

4.5K
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...
4.5K
Signal Flow Graphs01:18

Signal Flow Graphs

217
Signal-flow graphs offer a streamlined and intuitive approach to representing control systems, providing an alternative to traditional block diagrams. These graphs use branches to symbolize systems and nodes to represent signals, effectively illustrating the relationships and interactions within the system.
In a signal-flow graph, branches denote the system's transfer functions, while nodes represent the signals. The direction of signal flow is indicated by arrows, with the corresponding...
217
Perceiving Loudness, Pitch, and Location01:21

Perceiving Loudness, Pitch, and Location

211
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...
211
Parallel Processing01:20

Parallel Processing

150
The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
150

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

The visome: Using cognitive networks to examine lip-reading errors in English words.

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

Network science in experimental psychology.

Canadian journal of experimental psychology = Revue canadienne de psychologie experimentale·2025
Same author

Some challenges in using multilayer networks to bridge brain and mind.

Canadian journal of experimental psychology = Revue canadienne de psychologie experimentale·2024
Same author

The Effect of the COVID Pandemic on Clinical Psychology Research: A Bibliometric Analysis.

Behavioral sciences (Basel, Switzerland)·2024
Same author

Cognitive modelling of concepts in the mental lexicon with multilayer networks: Insights, advancements, and future challenges.

Psychonomic bulletin & review·2024
Same author

Speech, Language, and Hearing in the 21st Century: A Bibliometric Review of <i>JSLHR</i> From 2001 to 2021.

Journal of speech, language, and hearing research : JSLHR·2023
Same journal

Analysis of strength degradation of coal and rock masses and stability of mined areas under long term immersion environment.

PloS one·2026
Same journal

Biogenic Silver-Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus.

PloS one·2026
Same journal

Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium.

PloS one·2026
Same journal

Action-guilt, survivor-guilt, and depression in combat-related PTSD.

PloS one·2026
Same journal

Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.

PloS one·2026
Same journal

Deep learning based two-way feature depiction model for brain tumor detection.

PloS one·2026
查看所有相关文章

相关实验视频

Updated: Jun 29, 2025

Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology
05:38

Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology

Published on: June 29, 2021

2.4K

使用网络科学,用多层图形来检查视听语音感知.

Michael S Vitevitch1, Lorin Lachs2

  • 1University of Kansas, Lawrence, KS, United States of America.

PloS one
|March 29, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了AV-net,这是视觉语音感知 (唇读) 的模型,展示了听觉和视觉信息如何相互作用以改善词识别. 该模型有助于理解唇读和开发辅助技术.

更多相关视频

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
09:27

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

10.0K
Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

14.7K

相关实验视频

Last Updated: Jun 29, 2025

Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology
05:38

Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology

Published on: June 29, 2021

2.4K
Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
09:27

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

10.0K
Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

14.7K

科学领域:

  • 认知科学 认知科学
  • 计算神经科学是一种神经科学.
  • 语音处理 语音处理

背景情况:

  • 视觉语音感知或唇读对于理解口语至关重要,特别是在杂的环境中.
  • 现有的模型往往缺乏语音和视觉语音信息的整合.
  • 了解听觉和视觉线索之间的相互作用是改善语音感知的关键.

研究的目的:

  • 开发和评估模拟视觉语音感知的多层网络 (AV-net).
  • 在各种条件下,将AV-net的性能与人类的唇读能力进行比较.
  • 调查语音信息对视觉语音感知的影响.

主要方法:

  • 创建了一个多层的AV网络,其中听觉和视觉层分别代表声学和视觉信息.
  • 进行了激活扩散的计算机模拟,用于单词识别.
  • 模拟结果与人类在视听,仅视听和仅视觉条件下的表现进行了比较.
  • 对人类仅视觉读唇数据进行错误分析.

主要成果:

  • 视听网络展示了听觉和视觉信息的整合,以增强单词识别.
  • 模拟结果显示,在不同的呈现条件下,与人类参与者相比,性能可比.
  • 语音信息在多层网络中显著影响了视觉语音感知.

结论:

  • 该AV-net模型提供了关于视觉语音感知机制的见解.
  • 这些发现对唇读训练和辅助技术的发展有影响.
  • 该研究强调了整合语音和视觉信息对于强大的语音识别的重要性.