• Journal of the Korea Society of Computer and Information
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• v.29 no.7
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• pp.209-219
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• 2024

In this paper, we propose a study to investigate the significant impact of digital technology on the development of the cultural industry and tourism. By collecting, selecting, and analyzing data on digital music products from 281 cities in China from 2005 to 2022, we confirm that well-known digital music products play a crucial role in promoting domestic tourism economic growth. However, their impact on the international tourism economy is not significant. Furthermore, these well-known digital music products can not only promote the development of the regional tourism economy but also influence the tourism economy of neighboring cities. The promotional effect of well-known digital music products is particularly important in fourth- and fifth-tier cities with rich cultural diversity and abundant tourism resources. Overall, well-known digital music products have a positive role in stimulating market vitality and promoting regional tourism economic development. These findings provide an important foundation for the integrated development of culture and tourism in the digital age and offer valuable insights for upgrading regional industrial structures and fostering regional harmonious development.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.148-155
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• 2008

In this paper, we constructed the noise robust content-based music retrieval system in mobile environment. The performance of the proposed system was verified with ZCPA feature which is blown to have noise robust characteristic in speech recognition application. In addition, new indexing and fast retrieval method are proposed to improve retrieval speed about 99% compare to exhaustive retrieval for large music DB. From the computer simulation results in noise environment of 15dB - 0dB SNR, we confirm the superior performance of the proposed system about 5% - 30% compared to MFCC and FBE(filter bank energy) feature.

• Smart Media Journal
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• v.10 no.4
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• pp.80-90
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• 2021

Using optical music recognition technology based on deep learning, we propose to apply the results derived to VR games. To detect the music objects in the music sheet, the deep learning model used YOLO v5, and Hough transform was employed to detect undetected objects, modifying the size of the staff. It analyzes and uses BPM, maximum number of combos, and musical notes in VR games using output result files, and prevents the backlog of notes through Object Pooling technology for resource management. In this paper, VR games can be produced with music elements derived from optical music recognition technology to expand the utilization of optical music recognition along with providing VR contents.

• The Journal of Korea Robotics Society
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• v.8 no.3
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• pp.217-227
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• 2013

We introduce a learning system for the sight reading of simple drum sequences. Sight reading is a cognitive-motor skill that requires reading of music symbols and actions of multiple limbs for playing the music. The system provides knowledge of results (KR) pertaining to the learner's performance by color-coding music symbols, and guides the learner by indicating the corresponding action for a given music symbol using additional auditory or vibrotactile cues. To evaluate the effects of KR and guidance cues, three learning methods were experimentally compared: KR only, KR with auditory cues, and KR with vibrotactile cues. The task was to play a random 16-note-long drum sequence displayed on a screen. Thirty university students learned the task using one of the learning methods in a between-subjects design. The experimental results did not show statistically significant differences between the methods in terms of task accuracy and completion time.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.195-202
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• 2022

The purpose of this study is to study the perceived value of consumers of traditional Chinese music training institutions, and the resulting research on the impact of customers' purchase intentions. This research refers to relevant literature on customer perceived value and customer purchase intention, and divides customer perceived value into five value dimensions: emotion, quality, experience, price and reputation. Questionnaire survey method, using SPSS analysis AMOS tool to conduct empirical research, the research results show that customer perceived value has an important positive impact on purchase intention in five value dimensions of emotion, quality, price, experience and reputation, which is a traditional music training institution. Provide reference and suggestions for improvement.

• Korean Journal of Child Studies
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• v.22 no.4
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• pp.243-255
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• 2001

The aim of the study was to investigate whether music drama activity has an affect on literacy, musical ability and physical expression in preschoolers. The subjects of this experiment were 48 five-year-old children who were selected from two kindergarten in geonbook(experimental group : 24, comparison group : 24). The children in experimental group were asked to act four young children's music drama through sixteen weeks. The children in comparison group were involved in activity referred to in storybook. The data gained from the research were analyzed using a SPSS(p=.05) computer program. The main results in this study are as follows : First, there were partly significant differences in young children's music drama activity in terms of rating of literacy. Especially, story understanding as indicated by literacy test scores in the experimental group was significantly different. There were also significant differences in young children's music drama activity in terms of rating of musical ability and physical expression.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.149-158
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• 2015

This paper proposes a subband filtering technique to the MUSIC and the ESPRIT algorithm for estimating the magnitude and frequency of the harmonics of power signal. In proposed method, the input power signal is decomposed to the odd harmonics and the even harmonics respectively by the filter bank system. The amplitude and the frequency estimation of the decomposed harmonics are carried out using the MUSIC and the ESPRIT method. Subband filtering can reduce the autocorrelation matrix size of input data, and spectrum leakage between adjacent harmonics. Therefore, this subband technique has advantage in computational cost and estimation accuracy compared to fullband MUSIC and ESPRIT. To demonstrate the performance of the method, computer simulations are performed to the synthesized input signal, and experiment results are compared in subband and fullband cases.

• Journal of Information Processing Systems
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• v.11 no.3
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• pp.438-449
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• 2015

Recognition systems for scanned or printed music scores that have been implemented on personal computers have received attention from numerous scientists and have achieved significant results over many years. A modern trend with music scores being captured and played directly on mobile devices has become more interesting to researchers. The limitation of resources and the effects of illumination, distortion, and inclination on input images are still challenges to these recognition systems. In this paper, we introduce a novel approach for recognizing music scores captured by mobile cameras. To reduce the complexity, as well as the computational time of the system, we grouped all of the symbols extracted from music scores into ten main classes. We then applied each major class to SVM to classify the musical symbols separately. The experimental results showed that our proposed method could be applied to real time applications and that its performance is competitive with other methods.

• International journal of advanced smart convergence
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• v.6 no.2
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• pp.9-15
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• 2017

According to a recent survey, most elementary and secondary school students nationwide are stressed out by their academic records. Furthermore most of high school students in Korea have to study under the great duress. Some of them who can't overcome the academic stress finalize their life by suiciding. A study has found that it is one of the leading causes of stimulating the thought of committing suicide in Korean high school students. So it is necessary to reduce the high school student's suicide rate. Main content of this research is to implement a personalized music recommendation system. Music therapy can help the student deal with the stress, anxiety and depression problems. Proposed system works as a therapist. The music choice and duration of the music is adjusted based on the student's current emotion recognized automatically from EEG. If the happy emotion is not induced by the current music, the system would automatically switch to another one until he or she feel happy. Proposed system is personalized brain music treatment that is making a brain training application running on smart phone or pad. That overcomes the critical problems of time and space constraints of existing brain training program. By using this brain training program, student can manage the stress easily without the help of expert.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.1
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• pp.41-46
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• 2010

In this paper, the DoA(Direction of Arrival) estimator using unitary MUSIC algorithm is studied. The complex-valued correlation matrix of MUSIC algorithm is transformed to the real-valued one using unitary transform for easy implementation. The eigenvalue and eigenvector are obtained by the combined Jacobi-CORDIC algorithm. CORDIC algorithm can be implemented by only ADD and SHIFT operations and MUSIC spectrum computed by 256 point DFT algorithm. Results of unitary MUSIC algorithm designed by System Generator for FPGA implementation is entirely consistent with Matlab results. Its performance is evaluated through hardware co-simulation and resource estimation.