• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.5
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• pp.217-223
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• 2023

In this paper, we propose a new model for the conditional generation of music, considering key and rhythm, fundamental elements of music. MIDI sheet music is converted into a WAV format, which is then transformed into a Mel Spectrogram using the Short-Time Fourier Transform (STFT). Using this information, key and rhythm details are classified by passing through two Convolutional Neural Networks (CNNs), and this information is again fed into the Music Transformer. The key and rhythm details are combined by differentially multiplying the weights and the embedding vectors of the MIDI events. Several experiments are conducted, including a process for determining the optimal weights. This research represents a new effort to integrate essential elements into music generation and explains the detailed structure and operating principles of the model, verifying its effects and potentials through experiments. In this study, the accuracy for rhythm classification reached 94.7%, the accuracy for key classification reached 92.1%, and the Negative Likelihood based on the weights of the embedding vector resulted in 3.01.

• Journal of Advanced Navigation Technology
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• v.14 no.1
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• pp.108-118
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• 2010

In this paper, we propose Context-based Music Recommendation (COMUS) ontology for modeling user's musical preferences and context and for supporting reasoning about the user's desired emotion and preferences. The COMUS provides an upper Music Ontology that captures concepts about the general properties of music such as title, artists and genre and also provides extensibility for adding domain-specific ontologies, such as Mood and Situation, in a hierarchical manner. The COMUS is music dedicated ontology in OWL constructed by incorporating domain specific classes for music recommendation into the Music Ontology. Using this context ontology, we believe that the use of logical reasoning by checking the consistency of context information, and reasoning over the high-level, implicit context from the low-level, explicit information. As a novelty, our ontology can express detailed and complicated relations among the music, moods and situations, enabling users to find appropriate music for the application. We present some of the experiments we performed as a case-study for music recommendation.

• KIISE Transactions on Computing Practices
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• v.22 no.10
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• pp.479-487
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• 2016

People can listen to almost every type of music by music streaming services without possessing music. Ironically it is difficult to choose what to listen to. A music recommendation system helps people in making a choice. However, existing recommendation systems have high computation complexity and do not consider context information. Emotion is one of the most important context information of music. Lyrics can be easily computed with various language processing techniques and can even be used to extract emotion of music from itself. We suggest a music-level similarity evaluation method using emotion and structure. Our result shows that it is important to consider semantic information when we evaluate similarity of music.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1654-1659
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• 2003

In this paper, the performance evaluation of the JADE-MUSIC estimation based on the indoor channel is presented. By means of the JADE-MUSIC algorithm, DOA and time delay can be obtained simultaneously. In the JADE-MUSIC method, the channel impulse response is first estimated from the received samples and then this impulse response is employed to estimate DOAs and time delays of multipath waves. Moreover, according to the JADE-MUSIC characteristics, it can work in cases when the number of impinging waves is more than the number of antenna elements, unlike the traditional parametric subspace-based method, such a case is not true. Therefore, we employ the JADE-MUSIC algorithm applying for the real indoor environment where is rich of the multipath propagation waves and can imply that the number of waves is very possibly higher than that of the array element. The experiment is carried out in our laboratory considered to be the real indoor environment. The performance of the JADE-MUSIC algorithm is evaluated in terms of the comparison between the simulation and experiment results by using the simulated channel model and the real indoor channel model, respectively. It is clear that the joint angle and delay estimation using the simulated channel model are in good agreement with the estimation using the real indoor channel model. Therefore, we can say that the JADE-MUSIC algorithm accomplishes the high performance to jointly estimate the angle and delay of the arriving signal for the indoor environment.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.21-35
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• 2018

Since the introduction of MP3 players, CD recordings have gradually been vanishing, and the music consuming environment of music users is shifting to mobile devices. The introduction of smart devices has increased the utilization of music through music playback, mass storage, and search functions that are integrated into smartphones and tablets. At the time of initial MP3 player supply, the bitrate of the compressed music contents generally was 128 Kbps. However, as increasing of the demand for high quality music, sound quality of 384 Kbps appeared. Recently, music content of FLAC (Free License Audio Codec) format using lossless compression method is becoming popular. The download service of many music sites in Korea has classified by unlimited download with technical protection and limited download without technical protection. Digital Rights Management (DRM) technology is used as a technical protection measure for unlimited download, but it can only be used with authenticated devices that have DRM installed. Even if music purchased by the user, it cannot be used by other devices. On the contrary, in the case of music that is limited in quantity but not technically protected, there is no way to enforce anyone who distributes it, and in the case of high quality music such as FLAC, the loss is greater. In this paper, the author proposes an audio watermarking technology for copyright protection of high quality stereo music. Two kinds of information, "Copyright" and "Copy_free", are generated by using the turbo code. The two watermarks are composed of 9 bytes (72 bits). If turbo code is applied for error correction, the amount of information to be inserted as 222 bits increases. The 222-bit watermark was expanded to 1024 bits to be robust against additional errors and finally used as a watermark to insert into stereo music. Turbo code is a way to recover raw data if the damaged amount is less than 15% even if part of the code is damaged due to attack of watermarked content. It can be extended to 1024 bits or it can find 222 bits from some damaged contents by increasing the probability, the watermark itself has made it more resistant to attack. The proposed algorithm uses quantization in DCT so that watermark can be detected efficiently and SNR can be improved when stereo music is converted into mono. As a result, on average SNR exceeded 40dB, resulting in sound quality improvements of over 10dB over traditional quantization methods. This is a very significant result because it means relatively 10 times improvement in sound quality. In addition, the sample length required for extracting the watermark can be extracted sufficiently if the length is shorter than 1 second, and the watermark can be completely extracted from music samples of less than one second in all of the MP3 compression having a bit rate of 128 Kbps. The conventional quantization method can extract the watermark with a length of only 1/10 compared to the case where the sampling of the 10-second length largely fails to extract the watermark. In this study, since the length of the watermark embedded into music is 72 bits, it provides sufficient capacity to embed necessary information for music. It is enough bits to identify the music distributed all over the world. 272 can identify $4*10^{21}$, so it can be used as an identifier and it can be used for copyright protection of high quality music service. The proposed algorithm can be used not only for high quality audio but also for development of watermarking algorithm in multimedia such as UHD (Ultra High Definition) TV and high-resolution image. In addition, with the development of digital devices, users are demanding high quality music in the music industry, and artificial intelligence assistant is coming along with high quality music and streaming service. The results of this study can be used to protect the rights of copyright holders in these industries.

• Journal of the Korean Society for Library and Information Science
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• v.32 no.2
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• pp.5-34
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• 1998

The purpose of this study is to develop an idealistic scheme for the classification of Korean music. The ideal classification of Korean music should cover as much knowledge and materials of Korean music as possible. In this study, therefore, Korean music, Korean musicology and music materials were examined first as the backgrounds. Then classification schedules for Korean music including 679 Korean music of KDC were selected, and their expansion aspects and the problems were analyzed. The conditions and the possibility of developing an ideal classification schedule of Korean music were sought through reanalyzing the problems found in these existing classification schedules. As the result of this study a new classification schedule of Korean music was proposed.

• Journal of The Korean Association of Information Education
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• v.8 no.3
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• pp.405-414
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• 2004

Even if Internet has been used very much, there is no method of music aptitude test for children. We develop the music aptitude test in the internet to make music aptitude test easily. We test children for music aptitude early. We provide children the learning and instruction environment. This research makes children improve the ability of music. We develop the music aptitude test system for children in the WWW for children to use it. This system is expected to be a great help for children to test music aptitude easily. This system establish a well-understood and maintenance through this system for replacing the data files of their children in a effective way.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.81-88
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• 2019

Based on the theory of planned behavior and the theory of legal deterrence, this study takes consumers' willingness to pay for digital music as the research object, investigates the consumers who have digital music consumption channels and behaviors, and discusses the willingness of consumers to pay for digital music and its influencing factors. The study attempts to achieve the following research purposes: First, explore the influencing factors of willingness to pay for digital music using domestic and foreign literature research and related content analysis. Second, we want to examine the effect of Attitude, Collective Specifications, Quality Sensitivity and Music affinity on willingness to pay. Third, Legal deterrence and resource availability tries to verify whether there is a moderating effect between Attitude, Collective Specifications, Quality Sensitivity and Music affinity and willingness to pay. The research data was collected in 2019 between April 6th to May 8th. Questionnaires were randomly distributed in fixed places, mainly in Hubei Province, China. A total of 393 questionnaires were selected for data analysis. Based on the previous theoretical review and empirical analysis, the study draws the following conclusions: Firstly, attitude, collective specifications, quality sensitivity and music affinity have an impact on the willingness to pay. Second, Legal deterrence has a regulatory effect on the relationship among quality sensitivity, musical affinity and the willingness to pay. Last the resource availability has a significant impact on the willingness to pay. It also has a regulatory effect on the relationship among quality sensitivity, music affinity and the willingness to pay.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.19 no.2
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• pp.77-90
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• 2014

In the past composers used to make music with classical instruments such as piano, violin, guitar, flute, drums, and other well-known tools. With the advent of digital technology many software programs were developed which allow musicians to compose tunes using personal computers. Many file formats were introduced such as NIFF, SMDL and MIDI but none besides MIDI has been successful. Recently MusicXML has emerged as a de-facto standard for the computer representation of music. This paper presents a brief description of the structure of the MusicXML format and describes the development of a music score editor based on MusicXML. We implemented a MusicXML-based score editing software using C# language and a feasibility test showed the efficiency of our proposed method.