Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Method for classifying musical instrument signals

A classification method and signal technology, applied in the field of electronic information, can solve the problems of not well characterizing the signal difference, low accuracy of audio signal classification, complicated and tedious process of classifier parameter selection and operation, etc.

Inactive Publication Date: 2014-04-30
TAIYUAN UNIVERSITY OF SCIENCE AND TECHNOLOGY
View PDF1 Cites 12 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the existing research results, the classification accuracy of some audio signals is generally low, indicating that the above-mentioned audio characteristics do not describe the differences between all signals well, and the parameter selection and operation process of most classifiers There are complex and cumbersome shortcomings

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method for classifying musical instrument signals
  • Method for classifying musical instrument signals
  • Method for classifying musical instrument signals

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0051] We choose Matlab7.0 and Visual Studio2008 as the software platform, and program to realize the design of the scheme of the present invention. The implementation process is to select two common musical instrument signals: French horn and piano as the experimental objects. For each musical instrument signal, 10 sets of measured sample data are selected, and the sample data length is 2000 points. Among them, the first 8 groups are used as training samples, and the other 2 groups are used as test samples.

[0052] Take one sample of two instrument signals as an example to illustrate, the specific operation steps are as follows:

[0053] The sample signal is firstly processed by phase space reconstruction, then principal component analysis is performed to reduce redundancy, the principal component is extracted, and then enters the feature extraction part, and finally the musical instrument is recognized, and the neural network is trained by a flexible neural tree to achieve...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a method for classifying musical instrument signals, and belongs to the technical field of electronic information. Modules adopted in the method comprise a phase-space reconstruction module, a principal component analysis module, a feature extraction module and a flexibility neural tree module. The method is characterized by comprising the step of carrying out the phase-space reconstruction on a time sequence produced by different musical instrument sample signals, the step of removing redundant information through the principal component analysis to achieve the dimensionality reduction purpose, the step of depicting the differences of different musical instruments in the phase space through the probability density function by analyzing the features of various musical instruments, and the step of utilizing a flexible neural tree model to serves as a classifier to carry out classification. The method can effectively solve the problem of the high dependency of an artificial neural network structure, and the classification accuracy of a single musical instrument can reach up to 98.7 percent.

Description

technical field [0001] The invention belongs to the technical field of electronic information, and in particular relates to a classification method of musical instrument signals. Background technique [0002] Music is an integral part of people's lives. However, the only way for us to understand music information is through real-time audition to obtain the content we are interested in. With the development of science and technology, the information that people can access is also increasing rapidly. Therefore, it is not easy to obtain the music you are interested in through real-time audition in the massive data. In recent years, music data analysis and retrieval has become a research hotspot at home and abroad. [0003] Most music relies on the performance of musical instruments to express, and the same piece of music is played with different musical instruments, which will also bring different enjoyment to people's hearing. In the field of computer recognition, with the c...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G10L15/08
Inventor 郭一娜王志社郅逍遥王晓梅李临生
Owner TAIYUAN UNIVERSITY OF SCIENCE AND TECHNOLOGY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com