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

Double Resonance Techniques: Overview01:12

Double Resonance Techniques: Overview

197
Double resonance techniques in Nuclear Magnetic Resonance (NMR) spectroscopy involve the simultaneous application of two different frequencies or radiofrequency pulses to manipulate and observe two distinct nuclear spins. One important application of double resonance is spin decoupling, which selectively suppresses coupling with one type of nucleus while observing the NMR signal from another nucleus, simplifying the spectrum and enhancing resolution.
Spin decoupling is usually achieved by...
197
Perceiving Loudness, Pitch, and Location01:21

Perceiving Loudness, Pitch, and Location

205
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...
205
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

89
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
89
Classification of Signals01:30

Classification of Signals

435
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...
435
Amplifying Signals via Enzymatic Cascade01:22

Amplifying Signals via Enzymatic Cascade

8.5K
When a ligand binds to a cell-surface receptor, the receptor's intracellular domain changes shape, which may either activate its enzyme function or allow its binding to other molecules. The initial signal is amplified by most signal transduction pathways. This means that a single ligand molecule can activate multiple molecules of a downstream target. Proteins that relay a signal are most commonly phosphorylated at one or more sites, activating or inactivating the protein. Kinases catalyze...
8.5K
Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

226
In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
226

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

Multimodal Emotion Recognition Using Modality-Wise Knowledge Distillation.

Sensors (Basel, Switzerland)·2025
Same author

Speech Emotion Recognition Incorporating Relative Difficulty and Labeling Reliability.

Sensors (Basel, Switzerland)·2024
Same author

Improved Speech Spatial Covariance Matrix Estimation for Online Multi-Microphone Speech Enhancement.

Sensors (Basel, Switzerland)·2023
Same author

Affective Latent Representation of Acoustic and Lexical Features for Emotion Recognition.

Sensors (Basel, Switzerland)·2020
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
查看所有相关文章

相关实验视频

Updated: Jun 22, 2025

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
09:09

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Published on: September 27, 2024

440

后过器用于双通道语音增强使用连贯性和基于统计模型的噪声估计.

Sein Cheong1, Minseung Kim1, Jong Won Shin1

  • 1School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju 61005, Republic of Korea.

Sensors (Basel, Switzerland)
|June 27, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种新的语音增强后过器,使用连贯性和统计模型进行准确的噪音估计. 该方法可以在扩散噪声中提高语音质量,而不会通过方向干扰降低语音质量.

关键词:
一致性 连贯性 一致性双通道语音增强功能 双通道语音增强功能噪声PSD估计 噪声PSD估计后过器后过器的使用方法语音存在概率估计 语音存在概率估计

更多相关视频

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
08:42

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

Published on: September 3, 2021

3.1K
Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

1.5K

相关实验视频

Last Updated: Jun 22, 2025

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
09:09

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Published on: September 27, 2024

440
Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
08:42

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

Published on: September 3, 2021

3.1K
Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

1.5K

科学领域:

  • 信号处理 信号处理
  • 声学 声学 在声学方面
  • 语音技术 语言技术

背景情况:

  • 多通道语音增强系统依赖于空间波器和后波器来降低噪音.
  • 准确估计剩余噪声功率光谱密度 (PSD) 对于有效的后过至关重要.

研究的目的:

  • 为多通道语音增强提出一种新的后过器.
  • 开发基于连贯性和统计模型的后续语音存在概率 (SPP) 和噪音PSD的新估计器.

主要方法:

  • 以后使用麦克风信号之间的连贯性建模SPP,并将其与基于统计模型的SPP相结合.
  • 使用伪相干性推导出基于相干性的噪声PSD估计器,考虑光束转换器效应.
  • 结合基于连贯性和基于统计模型的噪声PSD估计器与拟议的SPP.
  • 修改了光谱增益函数,以纳入拟议的SPP.

主要成果:

  • 与现有方法相比,拟议的方法实现了更准确的噪声PSD估计.
  • 实验结果显示,在分散的噪音环境中,语音质量 (PESQ) 评分的感知评估得到了改善.
  • 在有方向干扰的情况下,该方法不会降低语音质量.

结论:

  • 提出的基于连贯性的方法提高了语音增强中的噪声估计准确性.
  • 新型后过器在各种噪音条件下有效地提高了语音质量.
  • 利用连贯信息为先进的语音增强系统提供了一个强大的策略.