Abstract
This article uses a multimodal smart music online teaching method combined with artificial intelligence to address the problem of smart music online teaching and to compensate for the shortcomings of the single modal classification method that only uses audio features for smart music online teaching. The selection of music intelligence models and classification models, as well as the analysis and processing of music characteristics, is the subjects of this article. It mainly studies how to use lyrics and how to combine audio and lyrics to intelligently classify music and teach multimodal and monomodal smart music online. In the online teaching of smart music based on lyrics, on the basis of the traditional wireless network node feature selection method, three parameters of frequency, concentration, and dispersion are introduced to adjust the statistical value of wireless network nodes, and an improved wireless network is proposed. After feature selection, the TFIDF method is used to calculate the weights, and then artificial intelligence is used to perform secondary dimensionality reduction on the lyrics. Experimental data shows that in the process of intelligently classifying lyrics, the accuracy of the traditional wireless network node feature selection method is 58.20%, and the accuracy of the improved wireless network node feature selection method is 67.21%, combined with artificial intelligence and improved wireless, the accuracy of the network node feature selection method is 69.68%. It can be seen that the third method has higher accuracy and lower dimensionality. In the online teaching of multimodal smart music based on audio and lyrics, this article improves the traditional fusion method for the problem of multimodal fusion and compares various fusion methods through experiments. The experimental results show that the improved classification effect of the fusion method is the best, reaching 84.43%, which verifies the feasibility and effectiveness of the method.
Highlights
The integration of artificial intelligence and education has triggered a change in the concept of music teaching in colleges and universities, the restructuring of the relationship between teachers and students, and the change of learning methods
Facing the opportunities and challenges brought by artificial intelligence technology, it is necessary to think about the value of artificial intelligence technology to the music teaching scene and method reform in colleges and universities, the integration of subject horizons, and the improvement of sight singing is given [1]
A multimodal smart music online teaching system and the implementation method for each module are introduced in this article
Summary
The integration of artificial intelligence and education has triggered a change in the concept of music teaching in colleges and universities, the restructuring of the relationship between teachers and students, and the change of learning methods. Since the MIDI data two-way switch has been developed successfully, wireless networked instruction in music schools has become a reality. They may freely share MIDI information with one another. The lyrics are represented using the vector space model (VSM) in artificial intelligence processing technology, which adds word frequency information and document frequency information as the weight of features.
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Computational and Mathematical Methods in Medicine
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
