 Analysis of the application of HMM algorithm in teaching musical note feature recognition in universitiesFei Huang and Meiqun Liao International Journal of Networking and Virtual Organisations, 2023, vol. 28, issue 2/3/4, 214-230 Abstract: With the rapid development of music education and information technology in colleges and universities, how to improve the efficiency of teachers' teaching in current music courses has increasingly become a focus of public attention. This study aims to propose an HMM algorithm based on the application of music note feature recognition teaching in colleges and universities. The experimental results show that the HMM algorithm is used in the music frequency sample signal after pre-processing, and its target accuracy is reached after 20 training sessions. Comparing the HMM algorithm with the other two algorithms, the results show that its correct rate is about 99.56%, and the probability of occurrence of insertion error and elimination error is 0.52% and 2.58%, which is better than the other two algorithms. In summary, it shows that the research proposed HMM algorithm has some practical value and relevance to the teaching of music in colleges and universities. Keywords: HMM algorithm; music teaching; feature recognition; fundamental frequency recognition method; pitch class profile; PCP. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijnvor:v:28:y:2023:i:2/3/4:p:214-230 Access Statistics for this article More articles in International Journal of Networking and Virtual Organisations from Inderscience Enterprises Ltd |
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