Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 3
776-780

Research on wood quality for musical instrument recognition using convolutional neural network

Huang Yinglai
Li Xiaoshuang
Zhao Peng
College of Information & Computer Engineering, Northeast Forestry University, Harbin 150040, China
DOI: 10.19734/j.issn.1001-3695.2017.10.0990

Abstract

At present, the vibration signal recognition algorithm for national musical instrument plate has the shortcomings of complex feature extraction and time-consuming. To solve this problem, this paper proposed a classification algorithm of wood vibration signal based on convolution neural network, to identify the quality of the musical instrument. Convolution neural network combined feature extraction and classification process to train the neural network, which owned the advantages of high recognition rate and good robustness. Firstly, this paper mainly analyzed and discussed spectrogram characteristics of the extraction of wood vibration signals. Then combining convolution neural network and grid search method, it could adjust the parameters. In order to avoid over-fitting, it obtained the final classification results by using new technologies such as ReLU and dropout. The experiments show that the accuracy of the test sample reaches 96%, which is obviously better than the traditional method. This method can reduce the error of manual measurement and speed up the selection time of the plate, and provide a more convenient method for the selection of the national musical instrument manufacturing field.

Foundation Support

国家自然科学基金资助项目(31670717)
国家教育部新世纪优秀人才专项基金资助项目(NCET-12-0809)
中央高校基本科研业务费专项基金资助项目(2572018BH03)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.10.0990
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 3
Section: Algorithm Research & Explore
Pages: 776-780
Serial Number: 1001-3695(2019)03-027-0776-05

Publish History

[2019-03-05] Printed Article

Cite This Article

黄英来, 李晓霜, 赵鹏. 卷积神经网络在乐器板材优劣识别中的应用研究 [J]. 计算机应用研究, 2019, 36 (3): 776-780. (Huang Yinglai, Li Xiaoshuang, Zhao Peng. Research on wood quality for musical instrument recognition using convolutional neural network [J]. Application Research of Computers, 2019, 36 (3): 776-780. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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