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

Force Classification01:22

Force Classification

1.0K
Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
1.0K
Perceiving Loudness, Pitch, and Location01:21

Perceiving Loudness, Pitch, and Location

160
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...
160

You might also read

Related Articles

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

Sort by
Same author

Teaching activity design and psychological practice of music majors under a convolutional neural network and transformer module.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: May 10, 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

Vocal performance evaluation of the intelligent note recognition method based on deep learning.

Dongyun Chang1

  • 1School of Music, Qinghai Normal University, Xining, China. 2020044@qhnu.edu.cn.

Scientific Reports
|April 22, 2025
PubMed
Summary

This study introduces an advanced deep learning model for accurate music note recognition and vocal performance evaluation. The attention mechanism-gated recurrent convolutional neural network (A-GRCNN) significantly improves accuracy and reliability in music information processing.

Keywords:
Attention mechanismDeep learningNeural networkNote recognitionVocal performance evaluation

More Related Videos

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.4K
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

309

Related Experiment Videos

Last Updated: May 10, 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
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.4K
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

309

Area of Science:

  • Music Information Retrieval
  • Deep Learning
  • Signal Processing

Background:

  • Accurate note recognition is crucial for vocal performance evaluation.
  • Traditional models often struggle with complex musical nuances.
  • Deep learning offers potential for enhanced music analysis.

Purpose of the Study:

  • To optimize note recognition and vocal performance evaluation accuracy.
  • To develop an intelligent note recognition model using deep learning.
  • To construct an optimized vocal performance evaluation model.

Main Methods:

  • Analysis of basic music theory.
  • Integration of convolutional neural networks (CNN) with gated recurrent units (GRU).
  • Implementation of an attention mechanism for an intelligent note recognition model (A-GRCNN).
  • Evaluation of model performance using F-value, accuracy, precision, and recall.
  • Comparison of different feature inputs, including Constant Q Transform (CQT).

Main Results:

  • The A-GRCNN model demonstrated superior performance across all evaluation metrics.
  • Achieved high accuracy (0.961), recall (0.958), F-value (0.963), and precision (0.970).
  • Multiple feature inputs, particularly CQT, significantly enhanced vocal performance evaluation accuracy.

Conclusions:

  • The A-GRCNN model represents a significant advancement in music note recognition and vocal performance evaluation.
  • Deep learning, especially with attention mechanisms, is highly effective for music information processing.
  • This research contributes to the application of deep learning in music and improves evaluation reliability.