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相关概念视频

Sound as Pressure Waves01:17

Sound as Pressure Waves

2.6K
Sound waves, which are longitudinal waves, can be modeled as the displacement amplitude varying as a function of the spatial and temporal coordinates. As a column of the medium is displaced, its successive columns are also displaced. As the successive displacements differ relatively, a pressure difference with the surrounding pressure is created. The gauge pressure varies across the medium.
The pressure fluctuation depends on the difference in displacements between the successive points in the...
2.6K
Sound Intensity00:58

Sound Intensity

4.2K
The loudness of a sound source is related to how energetically the source is vibrating, consequently making the molecules of the propagation medium vibrate. To measure the loudness of a source, the physical quantity of interest is the intensity. This is defined as the energy emitted per unit of time per unit of area perpendicular to the sound wave's propagation direction. Since the total energy is greater if the source vibrates for a longer duration and over a larger area, dividing the...
4.2K
Heart Sounds01:15

Heart Sounds

2.3K
Heart sounds are generated by the turbulence in blood flow due to the closing of heart valves. These sounds are best perceived slightly away from the valves, where the blood flow disseminates the sound.
Auscultation is the process of listening to these internal body sounds using a stethoscope. The heart produces four types of sounds, but only two—S1 and S2—can usually be heard with a stethoscope.
S1, also known as the "lub" sound, is caused by the closure of atrioventricular (A-V)...
2.3K
Perception of Sound Waves01:01

Perception of Sound Waves

4.7K
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...
4.7K
Sound Intensity Level00:53

Sound Intensity Level

4.3K
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...
4.3K
Sound Waves01:01

Sound Waves

9.5K
Sound waves can be thought of as fluctuations in the pressure of a medium through which they propagate. Since the pressure also makes the medium's particles vibrate along its direction of motion, the waves can be modeled as the displacement of the medium's particles from their mean position.
Sound waves are longitudinal in most fluids because fluids cannot sustain any lateral pressure. In solids, however, shear forces help in propagating the disturbance in the lateral direction as well....
9.5K

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相关实验视频

Updated: Sep 14, 2025

Assessment of Audio-Tactile Sensory Substitution Training in Participants with Profound Deafness Using the Event-Related Potential Technique
11:39

Assessment of Audio-Tactile Sensory Substitution Training in Participants with Profound Deafness Using the Event-Related Potential Technique

Published on: September 7, 2022

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史诗般的声音:一个大规模的行动数据集,声音的行动.

Jaesung Huh, Jacob Chalk, Evangelos Kazakos

    IEEE transactions on pattern analysis and machine intelligence
    |July 18, 2025
    PubMed
    概括

    我们介绍EPIC-SOUNDS,这是一个大型数据集,用于自我中心视频中的音频事件和动作识别. 这一数据集有助于开发纯粹从声音中理解行动的模型,推进视听研究.

    科学领域:

    • 计算机视觉 计算机视觉
    • 机器学习 机器学习
    • 音频信号处理 音频信号处理

    背景情况:

    • 以自我为中心的视频提供了丰富的第一人称视角.
    • 从音频线索中理解行动是人工智能的一个具有挑战性但至关重要的领域.

    研究的目的:

    • 介绍EPIC-SOUNDS,一个用于自我中心的视听动作识别的大型数据集.
    • 为音频事件和相关行动提供时间注释和类标签.
    • 促进对只有音频和视听行动理解的研究.

    主要方法:

    • 开发了一个注释管道,用于对音频段和动作描述的时间标签.
    • 将自由形式的音频描述分成44个不同的行动类别.
    • 收集并验证了对物体碰撞声音的材料注释.

    主要成果:

    • EPIC-SOUNDS包含78.4k个分类和39.2k个非分类的音频段.
    • 在数据集上评估了最先进的音频识别和检测模型.
    • 分析了时间相关性,模式相互作用和模型限制.

    结论:

    • EPIC-SOUNDS能够对基于音频的动作识别模型进行强有力的培训和评估.

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  • 突出了当前模型在理解基于声音的行动方面的潜力和局限性.
  • 为推进视听感知研究提供了宝贵的资源.