• Journal of Information Technology Applications and Management
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• v.23 no.1
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• pp.33-43
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• 2016

Along with the spread of digital music and recent growth in the digital music industry, the demands for music recommender are increasing. These days, listeners have increasingly preferred to digital real-time streamlining and downloading to listen to music because it is convenient and affordable for the listeners to do that. We use Bayesian learning through weight of listener's prefered music site such as Melon, Billboard, Bugs Music, Soribada, and Gini. We reflect most popular current songs across all genres and styles for music recommender system using user profile. It is necessary for us to make the task of preprocessing of clustering the preference with weight of listener's preferred music site with popular music charts. We evaluated the proposed system on the data set of music sites to measure its performance. We reported some of the experimental result, which is better performance than the previous system.

• Korean Journal of Child Studies
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• v.32 no.1
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• pp.1-11
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• 2011

This aim of this study was to investigate the effects of the music appreciation teaching-learning method on the musical ability of young children. The music appreciation activities were developed firstly in consideration of the 4 steps of the learning cycle (recognition, exploration, inquiry, application). One group was then taught music appreciation, taking into account the learning cycle. The results were then compared with another comparative group in terms of musical ability. The results indicated that the musical ability sum of the treatment groups improved more than the comparative group. More specifically, the treatment group for four-year-olds was seen to have improved significantly more than the comparative group in terms of musical ability. These results indicate that this music appreciation teaching-learning method has a number of positive effects upon young children`s musical ability. Therefore, it is suggested that kindergarten teachers conduct instruction with an appropriate accompanying learning cycle as part of the teaching-learning method when it comes to improving the musical ability of young children.

• Journal of the Korean association of regional geographers
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• v.1 no.1
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• pp.103-116
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• 1995

The purpose of this paper is to explore a brief review of trends in existing geographical research on music and to analyze music by the 5 themes of geography and to explore a variety of classroom techniques which examine song lyrics for their geographic content. The results of this paper are summarized as followed : Firstly, the trends in geographical research on music can be classified into five areas, the first is on spatial diffusion in music, the second on spatial diffusion in music, the third on regional division in music, the fourth on regional characteristics in music, the fifth on pedagogical tools in the teaching of geography. Secondly, music holds numerous possibilities for regional geographical study. The lyrics of music are littered with geographical term through which song writers impart image of culture, the distinct geographical nature of music lyrics gives rise to many geographical question, also, music lyrics gives place its special character. The results of analyses by the 5 themes of geography indicate that music are useful to learning of regional geography. The application of music to learning regional geography attracts much attentions. In the respect of importance of learning new regional geography, and in the respect of adapting globalization have to be focused on this subject.

• Journal of The Korean Association of Information Education
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• v.6 no.1
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• pp.42-52
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• 2002

For an effective listening to music, a repeated listening to music should be possible without any restriction of time and space as well as to music for a music class and the various multi-media learning materials for listening to music is required. However, an individualized and repeated listening is difficult and an individualized listening materials are lacking. To solve these problems, learning system for listening to music in elementary school sharing learning materials required for it and including learning factors of listening to music is required. Therefore, this study analyzes learning factors of listening to music in elementary school and the learning system for listening to music is designed and developed to make elementary students have their own active listening to music and feel achievement and confidence by teacher's evaluation of their writings after listening to music and experience a joyful musical activity. And it is applied to elementary school.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.300-308
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• 2021

The processes of informatization of the modern educational space are inextricably linked with the active introduction of innovative information technologies, which diversify the forms of education and upbringing. The use of these technologies in education due to their specific properties significantly enhances the clarity of learning, emotional impact on students, helps to deepen interdisciplinary links, intensifies students' work, and improves the organization of educational activities. Innovative information technologies offer new opportunities for the use of text, audio, graphic, and video information in lessons, enriching the methodological possibilities of the lesson. Today, the use of these technologies is becoming an integral part of the study of any subject. Using multimedia presentations, publications, and websites created by students in the learning process, they can develop learning skills. According to researchers, there are many multimedia programs for working with a computer in a music lesson, namely: a music player, a program for singing karaoke, a music constructor, music encyclopedias, and training programs. The introduction of innovative information technologies in the system of music education allows expanding learning opportunities.

• Journal of Music and Human Behavior
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• v.6 no.2
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• pp.1-23
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• 2009

This study aims to identify the effect of music psychotherapy on motivation for learning in the underachieving student. The study divided nine children into two groups and placed four children in a test group and five children in a control group. After conducting a pre-test, the researcher performed music psychotherapy with the four children in the test group for about 12 weeks, twice a week, totaling 18 sessions. Quantitative data were measured in pre-and-post tests using Mann-Whitney's U-test, and the effects of the therapy were analyzed using Wilcoxon. The findings of this study were as follows. Music psychotherapy was shown to be effective for improving all types of motivation for learning in underachieving students (p < .001). This was shown by assessing improvements in the experimental group across four sub-areas of motivation for learning (p < .1), and directly measured by examining the subjects' lingual responses related to motivation for learning. These results demonstrate that music psychotherapy is effective for enhancing motivation for learning in underachieving students.

• The Journal of Korean Association of Computer Education
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• v.14 no.4
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• pp.1-10
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• 2011

It is the basic direction of revised education course to bring up the autonomous and creative Koreans to lead the 21st century. In the music education of the middle school it could be said that music program using computer is a very effective medium for learners' sake of stimulating their audio-visual sense at the same time. In this study, I will look around the facility of the computer music program and tried to find the application method to connect the creative learning activity in music class. And I will also show the application method in the musical activity area. For this, I proposed the method for students' creative learning activity in the middle of using Finale 2010 for music notation, Window Moviemaker for image editing and Goldwave for sound editing.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.45-52
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• 2022

With the development of artificial intelligence analysis methods, especially machine learning, various fields are widely expanding their application ranges. However, in the case of classical music, there still remain some difficulties in applying machine learning techniques. Genre classification or music recommendation systems generated by deep learning algorithms are actively used in general music, but not in classical music. In this paper, we attempted to classify opera among classical music. To this end, an experiment was conducted to determine which criteria are most suitable among, composer, period of composition, and emotional atmosphere, which are the basic features of music. To generate emotional labels, we adopted zero-shot classification with four basic emotions, 'happiness', 'sadness', 'anger', and 'fear.' After embedding the opera libretto with the doc2vec processing model, the optimal number of clusters is computed based on the result of the elbow method. Decided four centroids are then adopted in k-means clustering to classify unsupervised libretto datasets. We were able to get optimized clustering based on the result of adjusted rand index scores. With these results, we compared them with notated variables of music. As a result, it was confirmed that the four clusterings calculated by machine after training were most similar to the grouping result by period. Additionally, we were able to verify that the emotional similarity between composer and period did not appear significantly. At the end of the study, by knowing the period is the right criteria, we hope that it makes easier for music listeners to find music that suits their tastes.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.27-32
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• 2024

Reliable and fine-grained musical metadata are required for efficient search of rapidly increasing music files. In particular, since the primary motive for listening to music is its emotional effect, diversion, and the memories it awakens, emotion classification along with genre classification of music is crucial. In this paper, as an initial approach towards a "ground-truth" dataset for music emotion and genre classification, we elaborately generated a music corpus through labeling of a large number of ordinary people. In order to verify the suitability of the dataset through the classification results, we extracted features according to MPEG-7 audio standard and applied different machine learning models based on statistics and deep neural network to automatically classify the dataset. By using standard hyperparameter setting, we reached an accuracy of 93% for genre classification and 80% for emotion classification, and believe that our dataset can be used as a meaningful comparative dataset in this research field.

• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.372-382
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• 2018

Understanding is the foundation of music appreciation, the ultimate goal of music learning. The purpose of this research was to create a model for the integration and implementation of Gordon's music learning theory principles into Suzuki violin instruction. This research shows how audiation can be taught within the framework of the Suzuki philosophy and curriculum. It is expected that Gordon's music learning theory can provide Suzuki teachers with unique capabilities for teaching musical understanding, specifically through the development of audiation. Through an audiation-based approach to Suzuki instruction, thus, young violinists will be able to learn to comprehend the tonal and rhythmic aspects of the music they perform. Future researchers may wish to assemble a more complete guide to the tonal and rhythm patterns used in the Suzuki repertoire. Furthermore, additional lesson plans and activities can and should be developed that represent the application of music learning theory to Suzuki violin instruction.