Application of Machine Learning Technology in Classical Music Education

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
Read More Add to Saved list
  • Author(s): Wang, Dongfang
  • Language:
    English
  • Source:
    International Journal of Web-Based Learning and Teaching Technologies. 2023 18(2).
  • Publication Date:
    2023
  • Document Type:
    Journal Articles
    Reports - Research
  • Additional Information
    • Availability:
      IGI Global. 701 East Chocolate Avenue, Hershey, PA 17033. Tel: 866-342-6657; Tel: 717-533-8845; Fax: 717-533-8661; Fax: 717-533-7115; e-mail: [email protected]; Web site: https://www.igi-global.com/journals/
    • Peer Reviewed:
      Y
    • Source:
      15
    • Subject Terms:
      Foreign Countries; Music Education; Classical Music; Musical Instruments; Educational Quality; Program Evaluation; Correlation; Artificial Intelligence; Educational Technology; Musical Composition; Music Techniques; Algorithms
    • Subject Terms:
      China
    • Accession Number:
      10.4018/IJWLTT.320490
    • ISSN:
      1548-1093
      1548-1107
    • Abstract:
      The goal is to promote the healthy and stable development of music education in China. The time-frequency sequence topology in frequency domain can improve the effect of convolution operation. Therefore, this paper applies the above algorithms to classical music education, including the recognition of classical instruments, the feature extraction and recognition of classical music, and the quality evaluation of classical music education. The quality of the music quality evaluation system can be judged according to the correlation between the output results and the subjective evaluation. The higher the correlation, the better the music quality evaluation method. Through relevant experiments, it is proved that DTW score alignment and end-to-end are more successful in extracting the features of classical music, and more accurate in identifying classical instruments. The objective evaluation method of pronunciation teaching quality is more objective and accurate than P.563 music teaching quality evaluation.
    • Abstract:
      As Provided
    • Publication Date:
      2023
    • Accession Number:
      EJ1387349