Application of Music Artificial Intelligence in Preschool Music Education

Yu, Lin; Ding, Jiaran

doi:10.1088/1757-899x/750/1/012101

Cited by 16 publications

(10 citation statements)

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“…This approach augments the conventional educational setting of a music history course, which depends on tangible materials, with an interactive educational context that raises students’ interest in this particular subject. Recently, Yu and Ding (2020) examined the use of Artificial Intelligence (AI) technology in supporting preschool music teaching in China. In simple terms, AI means the presence of brainpower in a mechanical apparatus.…”

Section: Literature Reviewmentioning

confidence: 99%

Exploring synergy in a mobile learning model for piano playing ornaments exercise with local musical heritage

Loo¹,

Chai

Loo

et al. 2021

International Journal of Music Education

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This study addresses the potential of a mobile learning model that integrates local Malaysian musical heritage in piano ornaments finger exercise. An asynchronous model adapted from the concept of karaoke was designed aiming at a synergy of piano exercise, edutainment, and heritage education with visual and auditory accompaniments. We aimed to raise interest and motivation for piano playing ornaments exercise among learners during practice while raising awareness of local musical heritage. A total of 30 piano students aged 13 to 15 years participated in this intervention study; they were equally divided into a control group and an experimental group. The pre- and post-intervention assessments revealed an increase in the levels of motivation, awareness of local musical heritage, and perceived satisfaction factors for the new mobile learning model.

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Section: Literature Reviewmentioning

confidence: 99%

Exploring synergy in a mobile learning model for piano playing ornaments exercise with local musical heritage

Loo¹,

Chai

Loo

et al. 2021

International Journal of Music Education

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show abstract

“…By actually playing, students are better able to comprehend the music theory that their teacher has taught them as well as the qualities and purposes of each musical element. The teacher can play a question in music class, then the students can play another response, or the teacher can play a piece of music, and then the students can repeat it or recreate it [ 2 , 3 ]. Both music students and music teachers benefit from the convenience that AI technology and music software combine to offer.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Construction of AI Environmental Music Education Application Model Based on Deep Learning

Cheng

Xiao

2022

Journal of Environmental and Public Health

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The art of music, which is a necessary component of daily life and an ideology older than language, reflects the emotions of human reality. Many new elements have been introduced into music as a result of the quick development of technology, gradually altering how people create, perform, and enjoy music. It is incredible to see how actively AI has been used in music applications and music education over the past few years and how significantly it has advanced. AI technology can efficiently pull in the course, stratify complex large-scale music or sections, simplify teaching, improve student understanding of music, solve challenging student problems in class, and simplify the tasks of teachers. The traditional music education model has been modified, and the music education model’s audacious innovation has been made possible by reducing the distance between the teacher and the student. A classification algorithm based on spectrogram and NNS is proposed in light of the advantages in image processing. The abstract features on the spectrogram are automatically extracted using the NNS, which completes the end-to-end learning and avoids the tediousness and inaccuracy of manual feature extraction. This study, which uses experimental analysis to support its findings, demonstrates that different music teaching genres can be accurately classified at a rate of over 90%, which has a positive impact on recognition.

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“…With the development of information technology and computer network technology, the traditional music teaching mode can no longer meet the needs of modern teaching, music online teaching has been popularized and developed, and a new learning mode that is di erent from the traditional one and is not limited by time and place is constructed [7]. Arranging harmony for melody is a key part of music creation, and it is also an extremely di cult job [8][9][10]. Only a few professional musicians can do this job, using arti cial intelligence technology to analyze music and learn complex harmony theory, and nally automatically [11].…”

Section: Introductionmentioning

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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Application of Music Artificial Intelligence in Preschool Music Education

Cited by 16 publications

References 0 publications

Exploring synergy in a mobile learning model for piano playing ornaments exercise with local musical heritage

Exploring synergy in a mobile learning model for piano playing ornaments exercise with local musical heritage

[Retracted] Construction of AI Environmental Music Education Application Model Based on Deep Learning

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

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