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

Extraction: Advanced Methods00:56

Extraction: Advanced Methods

392
Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
392
Amplifying Signals via Enzymatic Cascade01:22

Amplifying Signals via Enzymatic Cascade

8.2K
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...
8.2K
Upsampling01:22

Upsampling

171
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
171
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

1.6K
The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
1.6K
Hearing01:31

Hearing

51.3K
When we hear a sound, our nervous system is detecting sound waves—pressure waves of mechanical energy traveling through a medium. The frequency of the wave is perceived as pitch, while the amplitude is perceived as loudness.
51.3K
Auditory Pathway01:15

Auditory Pathway

4.5K
Auditory pathways constitute the complex neural circuits responsible for transmitting and interpreting auditory information from the peripheral auditory system to the brain. Sound waves are initially captured by the outer ear, funneled through the ear canal, and reach the tympanic membrane (eardrum). These vibrations are transmitted via the middle ear's ossicles to the inner ear's cochlea.
When viewed cross-sectionally, the cochlea reveals the scala vestibuli and scala tympani flanking...
4.5K

You might also read

Related Articles

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

Sort by
Same author

Research Progress on the Regulatory Role of Treg Cells in Inflammatory Eye Diseases.

Current issues in molecular biology·2026
Same author

SignMoD: Sign Language Video Generation via Mixture of Diffusion.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

Evolution and role of manganese-transforming bacterial microorganisms during natural manganese-tailing succession.

Journal of environmental sciences (China)·2026
Same author

A Rare Case of Descending Colon Metastasis Following Radical Nephroureterectomy for Left Ureteral Carcinoma: A Case Report and Literature Review.

Current oncology (Toronto, Ont.)·2026
Same author

Spectral Graph Features for Reference-free RNA 3D Quality Assessment.

bioRxiv : the preprint server for biology·2026
Same author

Chromosome-level genome assembly of Rhynchium brunneum (Fabricius, 1787) (Hymenoptera: Vespidae).

Scientific data·2026

Related Experiment Video

Updated: May 14, 2025

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

1.3K

Enhancing target speaker extraction with Hierarchical Speaker Representation Learning.

Shulin He1, Wei Xue2, Yang Yang1

  • 1College of Computer Science, Inner Mongolia University, Hohhot, China.

Neural Networks : the Official Journal of the International Neural Network Society
|April 11, 2025
PubMed
Summary
This summary is machine-generated.

Hierarchical Speaker Representation Learning (HSRL) improves target speaker extraction by capturing fine-grained acoustic and semantic features. This novel approach enhances performance beyond conventional single-vector embeddings.

Keywords:
Anchor informationAttentive recurrent networkSpeakerfilterTarget speaker extraction

More Related Videos

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

380
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

465

Related Experiment Videos

Last Updated: May 14, 2025

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

1.3K
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

380
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

465

Area of Science:

  • Speech processing
  • Machine learning
  • Artificial intelligence

Background:

  • Conventional target speaker extraction relies on single-vector embeddings, which may miss subtle acoustic details.
  • Existing methods do not leverage semantic information from auxiliary speech for improved extraction.

Purpose of the Study:

  • To propose a novel Hierarchical Speaker Representation Learning (HSRL) method for enhanced target speaker extraction.
  • To address limitations of conventional methods by incorporating both local acoustic and global semantic features.

Main Methods:

  • Developed a Hierarchical Speaker Representation Learning (HSRL) framework.
  • Implemented a Local Speaker Feature Extractor (LSFE) for fine-grained acoustic analysis.
  • Utilized ECAPA-TDNN within a Global Speaker Feature Extractor (GSFE) and introduced a Hierarchical Cascading Input Strategy (HCIS) to integrate features.

Main Results:

  • HSRL achieved significant performance improvements in target speaker extraction.
  • The proposed method established new optimal benchmarks on the Libri-2talker dataset.
  • Experimental results validated the effectiveness of integrating local and global speaker features.

Conclusions:

  • HSRL offers a more effective approach to target speaker extraction compared to traditional methods.
  • The combination of local acoustic and global semantic information is crucial for robust speaker extraction.
  • The proposed HCIS effectively guides global feature extraction with relevant semantic content.