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

Coarse emotion soft cutting and classification method for waveform music

A classification method and soft cutting technology, applied in speech analysis, speech recognition, instruments, etc., can solve inconvenient problems

Active Publication Date: 2014-04-09
黑盒子科技(北京)有限公司
View PDF4 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, for some existing research on music emotion recognition, the feature values ​​are extracted after the whole piece of music is processed as a whole, and the feature standards used are all unified.
These are sometimes inconvenient for the classification process of music pieces

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
  • Coarse emotion soft cutting and classification method for waveform music
  • Coarse emotion soft cutting and classification method for waveform music
  • Coarse emotion soft cutting and classification method for waveform music

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0054] figure 1 is a simplified process of the rough affective domain of the present invention; figure 2 It is the primary and secondary soft cutting of the music segment of the present invention; image 3 It is the change situation of the segment where the adjacent note comparison item of the present invention is located; Figure 4 It is a schematic diagram of the jump conditions of different coarse emotional domains in the present invention; Figure 5 It is a flow chart of identification steps of the present invention; Image 6 It is a soft cutting flow chart of the soft cutting process in the identification step of the present invention; Figure 7It is a secondary soft cutting flow chart of the soft cutting process in the recognition step of the present invention; as shown in the figure: a kind of waveform music rough emotion soft cutting classification method provided by the present invention comprises the following steps:

[0055] S1: Provide music data, and establis...

Embodiment 2

[0084] This embodiment 2 describes in detail the specific process of performing coarse emotional soft cutting of waveform music:

[0085] The music feature extraction step includes a Mallat algorithm-based time-frequency domain rapid decomposition step and a music feature extraction step.

[0086] Time-frequency domain fast decomposition steps based on Mallat algorithm:

[0087] Wavelet transform is a time domain-frequency domain analysis method, which overcomes the shortcomings of the FFT method using uniform resolution for high and low frequencies, and satisfies the requirements for high , low-frequency use of different resolution requirements. When the parameter becomes larger, the center frequency becomes smaller, the time domain bandwidth becomes wider, the frequency domain bandwidth becomes narrower, the time domain resolution becomes smaller, and the frequency domain resolution becomes larger. When the parameter becomes smaller, the center frequency becomes larger, and...

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 coarse emotion soft cutting and classification method for waveform music, belonging to the field of pattern recognition of computers. The coarse emotion soft cutting and classification of the waveform music are performed by a Mallat algorithm by aiming at music characteristic parameters, and the problem of accurate capture of waveform music characteristic emotion information used for a control system is solved. The method specifically comprises the following steps of (1) establishing a coarse emotion space domain; (2) pretreating; (3) extracting characteristics; (4) performing soft cutting; and (5) classifying. According to the method, the waveform music is processed by a time-frequency domain analysis method based on the Mallat algorithm, comparison parameter nodes with higher universality can be acquired by a samples training method according to two basic music characteristic quantities (intensity and rhythm), and skip conditions among all the emotion domains are determined according to the experience of experts, and effects of coarse emotion soft cutting and classification on the music are achieved finally.

Description

technical field [0001] The invention relates to a method for identifying music waveform files, in particular to a method for classifying rough and emotional soft cutting of waveform music. Background technique [0002] With the development of lighting technology, music and lighting performances have become an important project for stage performances, urban construction and scenic spot construction. At present, the manual classification and editing method used in the design of music and light show schemes has poor universality, inaccurate positioning, and consumes manpower and material resources. Under such circumstances, the designer hopes to quickly realize the emotional soft-cut classification of the entire performance music through the computer, which is in line with the emotional understanding of most people, so as to facilitate the designer to arrange lighting actions according to the music emotion faster and more accurately. [0003] However, for some existing researc...

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 Patents(China)
IPC IPC(8): G10L15/08G10L15/02G10L15/04G10L25/63G10L21/0208
Inventor 林景栋王唯廖孝勇林湛丁邱欣
Owner 黑盒子科技(北京)有限公司
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