Chinese traditional musical instrument classification method based on depth confidence network

A technology of deep belief network and musical instrument classification, which is applied in the field of musical instrument classification and deep learning, can solve the problems of difficult to find a unified model classification of different objects, time-consuming and labor-intensive problems, and achieve improved classification accuracy, simple method, and accurate classification Effect

Active Publication Date: 2017-01-11
NANJING UNIV OF SCI & TECH
View PDF3 Cites 29 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, most of the classification of musical instruments is based on manually selected acoustic features. Manually selecting features is time-consuming and laborious, and the features are diverse. It is difficult to find a unified model suitable for different objects for classification.

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
  • Chinese traditional musical instrument classification method based on depth confidence network
  • Chinese traditional musical instrument classification method based on depth confidence network
  • Chinese traditional musical instrument classification method based on depth confidence network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0032] combine figure 1 , the classification method of the traditional Chinese musical instrument based on deep belief network of the present invention, comprises the following steps:

[0033] Step 1. Preprocess the original audio files of traditional Chinese musical instruments, then divide them into frames, extract the primary features of each frame of audio files for input into the deep belief network, and add labels corresponding to the types of traditional Chinese musical instruments to each frame of audio files ; The specific steps are:

[0034] Step 1-1, removing the silent segment from the original audio file of the traditional Chinese musical instrument;

[0035] Step 1-2, divide the audio file from which the silent segment has been removed into a second segment, and unify each segment into a monophonic file with a sampling rate of bKHz. Where a is a fragment of a traditional Chinese musical instrument, which can be an integer between 10 and 50, and b is the samplin...

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 Chinese traditional musical instrument classification method based on a depth confidence network. During feature extraction of Chinese traditional musical instrument music, firstly, acoustic features of Chinese traditional musical instruments are extracted as primary features by employing a speech signal processing method, a depth learning network is constructed according to the depth confidence network, and more abstract features are extracted from the primary features of the Chinese traditional musical instruments by employing the depth learning network; and reconstruction abstract features of the Chinese traditional musical instruments are input to a softmax layer to predict the belonged type of the corresponding played musical instrument. The method is simple and feasible, the classification accuracy of the Chinese traditional musical instruments is improved, and more effective information is provided for the field of music information retrieval.

Description

technical field [0001] The invention belongs to the field of musical instrument classification and deep learning, in particular to a classification method of traditional Chinese musical instruments based on a deep belief network. Background technique [0002] With the development of computer networks and digital music, music data analysis and retrieval has become a hot research field in recent years. There are many content-based music information retrieval, such as music genre classification, singer identification, etc. Among them, the classification of musical instruments is also a very important field of music information retrieval, which is very important for the recognition and classification of music genres, emotions, scenes, etc. For example, when performing music genre classification, if the musical instrument used in the music file is known, using this information can improve the classification accuracy of the music genre. [0003] Although the classification of mus...

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): G10L15/02G10L15/06G10L15/08G10L25/12G10L25/24
CPCG10L15/02G10L15/063G10L15/08G10L25/12G10L25/24G10L2015/0631
Inventor 李彧晟王芳朱雨倩季文韬周志强洪弘顾陈
Owner NANJING UNIV OF SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products