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

Integrator and Differentiator01:13

Integrator and Differentiator

771
Op-amp circuits have significant applications in various fields, including automotive engineering. One such application is cruise control systems in cars, where op-amp circuits are integral for maintaining a constant speed. In these systems, op-amps function as both integrators and differentiators.
An integrator within an op-amp circuit produces an output directly proportional to the integral of the input signal. This is achieved by replacing the feedback resistor in a typical inverting...
771
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

96
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
96
Design Example01:23

Design Example

316
The innovation of touch-tone telephony revolutionized the telecommunications industry by replacing the traditional rotary dial with a dual-tone multi-frequency (DTMF) signaling system. This system uses a matrix-style keypad with buttons arranged in four rows and three columns, creating 12 distinct signals each assigned to a pair of frequencies. Each button press results in a simultaneous generation of two sinusoidal tones – one from a low-frequency group (697 to 941 Hz) and one from a...
316
Perceiving Loudness, Pitch, and Location01:21

Perceiving Loudness, Pitch, and Location

194
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...
194
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

173
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
173
Double Resonance Techniques: Overview01:12

Double Resonance Techniques: Overview

191
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...
191

You might also read

Related Articles

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

Sort by
Same author

Shengxian decoction suppresses malignant progression of lung adenocarcinoma by enhancing CD8<sup>+</sup> T cell function via the FYN-PI3K/AKT axis.

Chinese medicine·2026
Same author

Three-dimensional correction of cubitus varus deformity using patient-specific 3D-printed osteotomy guides.

Frontiers in surgery·2026
Same author

NL-YOLOv5: a model with a larger receptive field and the ability to globally acquire features.

Frontiers in neurorobotics·2026
Same author

Urodynamic characteristics of different types of detrusor overactivity in patients with benign prostatic obstruction.

Frontiers in urology·2026
Same author

OACodec: Audio attribute disentanglement via orthogonal disentanglement and mutual information minimization.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

Snoring-based obstructive sleep apnea screening and AHI estimation with an adapted pretrained audio model.

Physiological measurement·2026

Related Experiment Video

Updated: Jun 6, 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

403

A Feature Integration Network for Multi-Channel Speech Enhancement.

Xiao Zeng1, Xue Zhang1, Mingjiang Wang1

  • 1Key Laboratory for Key Technologies of IoT Terminals, Harbin Institute of Technology, Shenzhen 518055, China.

Sensors (Basel, Switzerland)
|November 27, 2024
PubMed
Summary

This study introduces a novel network for multi-channel speech enhancement, improving spectral feature extraction using shifted-window self-attention. The proposed model effectively refines speech signals in noisy environments, achieving competitive performance.

Keywords:
LSTMdeep learningmulti-channel speech enhancementself-attention

More Related Videos

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

1.4K
Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages
06:04

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages

Published on: March 24, 2023

339

Related Experiment Videos

Last Updated: Jun 6, 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

403
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

1.4K
Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages
06:04

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages

Published on: March 24, 2023

339

Area of Science:

  • Signal Processing
  • Machine Learning

Background:

  • Multi-channel speech enhancement is crucial for recovering speech from noise.
  • Recent methods leverage spectral information for improved performance.

Purpose of the Study:

  • Propose a novel feature integration network for enhanced speech signal recovery.
  • Improve precision in feature extraction using advanced attention mechanisms.

Main Methods:

  • Developed a network integrating full- and sub-band LSTM modules for spectral information capture.
  • Employed a global-local attention fusion module with a dual-branch architecture.
  • Utilized shifted-window-based self-attention for feature refinement and spatial attention for fusion.
  • Trained the model to predict the complex ratio mask (CRM) for signal enhancement.

Main Results:

  • Ablation studies confirmed significant performance contributions from each module.
  • The model achieved competitive results on the SPA-DNS and Libri-wham datasets.
  • Demonstrated enhanced quality and precision in speech signal recovery.

Conclusions:

  • The proposed feature integration network effectively enhances multi-channel speech.
  • Shifted-window self-attention and attention fusion modules are key to performance improvements.
  • The model shows promise for real-world applications in noisy conditions.