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

6.0K
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...
6.0K
Perceiving Loudness, Pitch, and Location01:21

Perceiving Loudness, Pitch, and Location

1.3K
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...
1.3K

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

Invoking ferroptosis and photon-controlled pyroptosis <i>via</i> an integrated therapeutic system for triple-pathway tumor therapy.

Chemical science·2026
Same author

Wedelactone-loaded exosomes for sepsis-induced liver injury: a novel therapeutic strategy.

Drug delivery·2026
Same author

A large-scale retrospective analysis reveals the fungal pathogen spectrum across diverse clinical specimens using metagenomic next-generation sequencing.

Frontiers in cellular and infection microbiology·2026
Same author

The impact of physical activity and psychosocial factors on osteoarthritis risk.

Experimental gerontology·2026
Same author

Development and external validation of the HCH and HPMS prognostic indices for sepsis: a retrospective model development study using a Multi-Objective Non-Newtonian Fluid optimization algorithm.

BMC medical informatics and decision making·2026
Same author

Universal In Situ Flowrate Monitoring for Piezoelectric Microfluidics via Triboelectric Self-Sensing.

Advanced materials (Deerfield Beach, Fla.)·2026

相关实验视频

Updated: Apr 7, 2026

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

14.6K

基于多任务学习的场景依赖的声音事件检测,具有可变形的大内核注意力卷积.

Haiyue Zhang1, Menglong Wu1, Xichang Cai1

  • 1School of Information Science and Technology, North China University of Technology, Beijing, China.

PloS one
|May 9, 2025
PubMed
概括
此摘要是机器生成的。

本研究引入了一种新的多任务学习网络,用于声事件检测 (SED) 和声场景分类 (ASC). 这种新的方法通过利用场景信息和先进的特征提取技术,显著提高了SED的性能.

更多相关视频

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

432
Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

4.5K

相关实验视频

Last Updated: Apr 7, 2026

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

14.6K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

432
Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

4.5K

科学领域:

  • 环境健全性分析环境健全性分析
  • 机器学习 机器学习
  • 深度学习是一种深度学习.

背景情况:

  • 声事件检测 (SED) 和声场景分类 (ASC) 是环境声音分析中的相关任务.
  • 以前的多任务学习 (MTL) 方法经常使用硬参数共享,限制SED和ASC之间的特征交换和信息流.
  • 这阻碍了平衡复杂的相互关系和优化两个任务的性能的能力.

研究的目的:

  • 为联合SED和ASC提出一个新的多任务网络.
  • 通过利用声学场景信息来提高声音事件检测性能.
  • 改进相关音频分析任务之间的功能共享和信息流.

主要方法:

  • 开发了一个残留多层特征提取 (R-MFE) 框架,用于联合SED和ASC.
  • 引入了D-LKAC注意力模块,将自我注意力和卷积结合起来,用于全球和本地特征捕获.
  • 整合了MS-conv模块,从多个维度捕获音频细节,进一步增强SED.

主要成果:

  • 拟议的MTL方法在TUT Acoustic Scenes 2016/2017和TUT Sound Events 2016/2017数据集上进行了评估.
  • 实验结果表明,与最先进的技术相比,性能优越.
  • 在共同任务中,F分数显著提高了6.44%.

结论:

  • 新的R-MFE框架有效地解决了环境声音分析中以前的MTL方法的局限性.
  • 提出的注意力和卷积模块增强了模型捕捉相关音频特征的能力.
  • 这种方法表明了改善联合声事件检测和声场景分类的有希望的方向.