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: 2013-02-13
黑盒子科技(北京)有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

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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 pro

Method used

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  • 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

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Experimental program
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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 flowchart 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 7 It 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 establish ...

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. This method overcomes the shortcomings of the FFT method using uniform resolution for high and low frequencies. , 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 time-domain The bandwidth be...

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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

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Application Information

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IPC IPC(8): G10L15/08G10L15/02G10L15/04G10L15/06
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
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