• The Journal of the Korea Contents Association
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• v.12 no.3
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• pp.102-113
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• 2012

The effort to generate new values in this age of digital technology characterized by rapid changes in information and knowledge demands transformations not only in the sociocultural and educational spheres but also specifically in the field of arts and culture education. One of the greatest transformations is emphasis on integration and consilience among different fields which has impacted the field of arts and culture, giving birth to the practice of arts and culture education. Digital technology actively utilizes in lots of subjects, which, also becomes a challenging factor for the field of arts and culture education. In this context, this study theoretically considered to approach music technology to use for the field of arts and culture education. Utilization of music technology takes interdisciplinary approaches combining various subjects in the field of arts and culture education. Considering the current circumstances in which there is a lack of teaching and learning methodologies which reflect the unique, specialized nature and the intrinsic originality of the field of arts and culture education. It is deemed that by accumulating more case studies applying music technology in practice to a wider variety of targets and situations. Music technology will serve the role of an important a learning tool for the arts and culture education field.

• 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 Institute of Intelligent Systems
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• v.26 no.6
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• pp.445-451
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• 2016

This paper introduces a postprocessing method, an iteration method for melody, and an average neural network method for learning a large number of songs in order to improve musically insufficient parts in automatic composition using existing artificial neural network. The melody of songs composed by artificial neural networks is produced according to the melodies of trained songs, so it can not be a specific tonality and it is difficult to have a repetitive composition. In order to solve these problems, we propose a postprocessing method that converts the melody composed by artificial neural networks into a melody having a specific tonality according to music theory and an iteration method for melody by iteratively composing measure divisions of artificial neural networks. In addition, the existing training method of many songs has some disadvantages. To solve this problem, we adopt an average neural network that is made by averaging the weights of artificial neural networks trained each song. From some experiments, it was confirmed that the proposed method solves the existing problems.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.142-147
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• 2008

In this paper, we propose a novel a roach to improve the performance of speech/music classification for the selectable mode vocoder (SMV) of 3GPP2 using the support vector machine (SVM). The SVM makes it possible to build on an optimal hyperplane that is separated without the error where the distance between the closest vectors and the hyperplane is maximal. We first present an effective analysis of the features and the classification method adopted in the conventional SMV. And then feature vectors which are a lied to the SVM are selected from relevant parameters of the SMV for the efficient speech/music classification. The performance of the proposed algorithm is evaluated under various conditions and yields better results compared with the conventional scheme of the SMV.

• Review of Culture and Economy
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• v.21 no.2
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• pp.111-139
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• 2018

This study is about classical music lovers who write a lengthy concert review on instagram. The intention and objective of writing a review is discussed in addition to inter-communication between those reviewers. For the analysis, an interview with 8 reviewers are mainly analyzed with their reviews. As a result, it is found that some affordances of Instagram, easiness, randomness, and friendliness affects them to use Instagram more than other social media. Hence, since Instagram is image-based platform, it helps writers to keep their reviews from getting an attention by other users. Because of their sense of inferiority that they are lacking in classical music knowledge, continuous writing and reading of reviews help them accumulating some amount of cultural capital needed for understanding classical music in a proper way.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.57-64
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• 2024

This paper aims to enhance the accuracy of music genre classification for music tracks where genre information is not provided, by utilizing machine learning to classify a large amount of music data. The paper proposes collecting and preprocessing data instead of using the commonly employed GTZAN dataset in previous research for genre classification in music. To create a dataset with superior classification performance compared to the GTZAN dataset, we extract specific segments with the highest energy level of the onset. We utilize 57 features as the main characteristics of the music data used for training, including Mel Frequency Cepstral Coefficients (MFCC). We achieved a training accuracy of 85% and a testing accuracy of 71% using the Support Vector Machine (SVM) model to classify into Classical, Jazz, Country, Disco, Soul, Rock, Metal, and Hiphop genres based on preprocessed data.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.06a
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• pp.412-415
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• 2001

본 연구는 초등 음악과 창작 학습을 위한 멀티미디어 활용과 그 효과를 알아보기 위하여 멀티미디어 활용 집단과 전통적인 수업 집단으로 구분하여 극용하고 학업성취도를 비교 분석해 보는 것을 목적으로 하였다. 멀티미디어 활용은 Noteworthy 1.70b를 이용하였다. 연구 대상은 부산광역시 장전초등학교 6학년 학생이며, 두 집단으로 구분하여 실시하였다. 연구의 가설로는 멀티미디어 활용 집단의 학업 성취도가 전통 수업 집단의 성취도보다 높을 것이라고 설정하였고, 결과 분석은 SAS(통계분석프로그램)를 사용하였다. 연구 결과 멀티미디어 활용 학습은 학습 집단 전체에 대한 학업 성취도를 균등하게 향상시킬 수 있다는 결론을 내릴 수 있었다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.12
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• pp.345-351
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• 2016

The purpose of this study is to provide methods to improve the teaching of piano technique of intermediate-level learners through the works of Stephen Heller by focusing on rhythm and balance. Although a romantic-era composer, Stephen Heller's works are not well-known. However, when analyzing his compositions, many require the player to focus on their foundational piano techniques and musicality. Heller composed many interesting works including etudes that allow intermediate-level pianists to develop their musicality as much as those playing Chopin or Liszt from the same era. This study presents teaching methods for developing piano technique by focusing on rhythm and balance, and for enhancing musicality to improve the quality and significance of piano education and pedagogical research.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.207-213
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• 2024

In this paper, we study how to improve the performance of a machine learning-based automatic music transcription model by adding musical information to the input data. Where, the added musical information is information on the number of pitches that occur in each time frame, and which is obtained by counting the number of notes activated in the answer sheet. The obtained information on the number of pitches was used by concatenating it to the log mel-spectrogram, which is the input of the existing model. In this study, we use the automatic music transcription model included the four types of block predicting four types of musical information, we demonstrate that a simple method of adding pitch number information corresponding to the music information to be predicted by each block to the existing input was helpful in training the model. In order to evaluate the performance improvement proceed with an experiment using MIDI Aligned Piano Sounds (MAPS) data, as a result, when using all pitch number information, performance improvement was confirmed by 9.7 % in frame-based F1 score and 21.8 % in note-based F1 score including offset.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.988-991
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• 2014

일반적으로 인간은 원하는 정보를 얻거나 어려운 계산과정을 더 빠르고 쉽게 처리하기 위해 컴퓨터를 사용한다. 또한 컴퓨터를 이용해 자연 속에서 일어나는 일들을 과학적으로 분석하여 시뮬레이션을 하기도 한다. 본 연구는 인간의 전유물로 여겨졌던 예술적 창작 활동을 컴퓨터로 모방하는 실험이다. 작곡가가 음악을 통해 음악의 특성을 학습하여 새로운 곡을 작곡하는 과정을 컴퓨터로 모방해보았다.