A New Music Teaching Mode Based on Computer Automatic Matching Technology

Zhang, Yingxue; Ding, Yi

doi:10.3991/ijet.v16i16.24895

Cited by 16 publications

(11 citation statements)

References 35 publications

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“…Williams et al [17] proposed a feature representationbased music summarization algorithm, and an algorithm for extracting choruses in music was proposed earlier, and they achieved good results in the typical music structure. e detection rate of chorus on the self-built test set has achieved an 80% detection rate, but this work is limited to its analysis [18]. On the basis of subtraction, the candidate fundamental frequency is extracted from the harmonic product spectrum, and the overlapping harmonics are separated by harmonic reset [19].…”

Section: Related Workmentioning

confidence: 99%

Interactive Teaching Based on Artificial Intelligence and Its Application in Improving National Music Appreciation Ability

Zhang

2022

Mathematical Problems in Engineering

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The limitations of the traditional interactive teaching model are gradually becoming apparent in the current music teaching process. Based on the interactive teaching theory of artificial intelligence, this paper constructs an evaluation model of ethnic music appreciation ability and conducts research by using a novel method of fusion of long- and short-term audio features. The model proposes the classical features describing the sound quality and the beat histogram as the feature of the long-term rhythm of the music to form a mixed feature; secondly, the representation method of the song style vector is proposed, and the quantitative problem of music teaching is solved. During the simulation process, the model adopts the popular Model-View-Controller (MVC) design pattern and Unified Modeling Language (UML) and is developed with the Java 2 Platform Enterprise Edition (J2EE) architecture. It realized the user login function of three identities of students, teachers, and system administrators, and the subsystem can complete the management of students’ personal information, browse related courseware information and other resource information, and download courseware and tutorials. The experimental results show that the average value of the students’ evaluation is 0.606; the average value of case is 0.5852; it also reduces the workload of later maintenance of the system.

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Section: Related Workmentioning

confidence: 99%

Interactive Teaching Based on Artificial Intelligence and Its Application in Improving National Music Appreciation Ability

Zhang

2022

Mathematical Problems in Engineering

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“…Only by fully utilising current new media technology will music education reform achieve the desired outcomes. As a result of the current educational reform, the vast majority of colleges and universities have begun to use new media resources to implement music teaching reform in order to achieve better teaching effects, resulting in a comprehensive music curriculum reform [11].…”

Section: Problems Of Musicmentioning

confidence: 99%

Research on the Innovation of Music Teaching in Universities Based on Artificial Intelligence Technology

Shi

Ning

2022

Security and Communication Networks

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At present, music education in colleges is in a period of rapid development in China. At the same time, music education in universities is facing innovation and reform of teaching modes. How to improve music education in colleges and universities has become an important issue for music teachers in colleges. Music teaching and management activities for students in general universities can enrich students’ talents and expand their knowledge. It can also help them develop a positive emotional psychology and develop positive and healthy character characteristics, both of which are vital for college students’ healthy development. Innovation and modification in music teaching and management activities for students is the only way to increase the quality and effectiveness of music teaching for nonarts students and to promote the overall quality of students. Based on this, this paper proposes an innovative research method of college music teaching based on artificial intelligence technology. The method introduces a fuzzy evaluation algorithm to establish a two-level teaching evaluation index system and calculates the weights of each index based on fuzzy mathematical theory. In data processing, the SVM algorithm in the field of data mining is used to classify all collected teaching evaluation data in advance through supervised learning, which significantly improves the efficiency of data processing. The experimental results show that the model in this paper can well assess the quality of music teaching in colleges and universities and play a role in promoting the progress of music teaching in colleges and universities.

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“…It has the characteristics of classical elegance and can cultivate students' own traditional cultural heritage. When teaching guzheng knowledge, teachers can cultivate students' interest in learning through the beautiful and pleasant music played by guzheng strings, create a harmonious classroom learning atmosphere, and enable students to deeply feel the beauty of guzheng music [8][9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Challenges and Optimization Paths of Guzheng Professional Education in Colleges under Big Data Era

2022

Journal of Environmental and Public Health

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As a treasure among Chinese national musical instruments, guzheng is an important part of traditional Chinese music. As the art of national music goes to the world, the art of guzheng has been widely promoted. As the best form to carry forward the art of guzheng, the teaching of guzheng majors in colleges is significant in teaching and continuously improves guzheng art accomplishment. Oral teaching and step-by-step music theory and technique teaching are typical ways of teaching musical instrument performance in colleges. However, under big data, Chinese education is undergoing a profound change, and the combination of big data and education has become a new contemporary education method. This work studies the guzheng professional education in colleges under big data. First, this work aims at the existing outstanding issues of guzheng teaching in colleges and studies the challenges and optimization paths of guzheng professional education in colleges under big data. Second, this work proposes a multiscale residual attention fusion network (MSRAFNET) to evaluate the teaching quality of guzheng majors in colleges in the era of big data. The feature extraction of the network model is mainly completed by the residual module, which is composed of several multiscale residual learning units. Adding an attention mechanism to the multiscale residual learning unit can enhance the feature extraction of key information by the network and reduce the interference of redundant information, which is more conducive to the learning of data features. It adopts the design of GAP and Dropout to reduce spatial parameters in network training, and the effect of antioverfitting is better. Third, this work systematically evaluates the optimization path of Guzheng education and MSRAFNET, and the systematic experiments verify the superiority of the designed method.

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A New Music Teaching Mode Based on Computer Automatic Matching Technology

Cited by 16 publications

References 35 publications

Interactive Teaching Based on Artificial Intelligence and Its Application in Improving National Music Appreciation Ability

Interactive Teaching Based on Artificial Intelligence and Its Application in Improving National Music Appreciation Ability

Research on the Innovation of Music Teaching in Universities Based on Artificial Intelligence Technology

[Retracted] Challenges and Optimization Paths of Guzheng Professional Education in Colleges under Big Data Era

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