• Journal of Music and Human Behavior
• /
• v.12 no.2
• /
• pp.61-77
• /
• 2015

The purpose of this study was to investigate music therapists'use and perception of computer-based music technology. Questionnaires were distributed either electronically or in-person to 367 music therapists with credentials. Of the 367 initially distributed questionnaires, 101 were returned and 61 were analyzed after excluding 40 incomplete responses. The survey was comprised of two sections: the use of music technology and perceived importance of music technology in music therapy practice. The results showed that 65.6% of the respondents had used music technology in their clinical practice. The most frequently used type of music technology was Finale, followed by Garage band, and Cubase. With regard to the areas where music technology was used, it was implemented primarily for adolescents for musical or emotional goals, and was applied most frequently as a musical resource. In addition, most respondents showed a positive attitude toward music technology and added that they would need to be trained to use music technology for their clinical practice. These results provide practical information on how music therapists use and perceive computer-based music technology, and its implication for music therapy clinical practice.

• Journal of Information Technology Applications and Management
• /
• v.23 no.1
• /
• pp.33-43
• /
• 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
• /
• v.20 no.10
• /
• pp.69-76
• /
• 2015

User's selection of music is largely influenced by private tastes as well as emotional states, and it is the unconsciousness projection of user's emotion. Therefore, we think user's emotional states to be music itself. In this paper, we try to grasp user's emotional states from music selected by users at a specific context, and we analyze the correlation between its context and user's emotional state. To get emotional states out of music, the proposed method extracts emotional words as the representative of music from lyrics of user-selected music through morphological analysis, and learns weights of linear classifier for each emotional features of extracted words. Regularities learned by classifier are utilized to calculate predictive weights of virtual music using weights of music chosen by other users in context similar to active user's context. Finally, we propose a method to recommend some pieces of music relative to user's contexts and emotional states. Experimental results shows that the proposed method is more accurate than the traditional collaborative filtering method.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.11 no.2
• /
• pp.124-128
• /
• 2011

Music emotion recognition is currently one of the most attractive research areas in music information retrieval. In order to use emotion as clues when searching for a particular music, several music based emotion recognizing systems are fundamentally utilized. In order to maximize user satisfaction, the recognition accuracy is very important. In this paper, we develop a new music emotion recognition system, which employs a multilabel feature selector and multilabel classifier. The performance of the proposed system is demonstrated using novel musical emotion data.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.15 no.3
• /
• pp.159-165
• /
• 2015

The need for the recognition of music emotion has become apparent in many music information retrieval applications. In addition to the large pool of techniques that have already been developed in machine learning and data mining, various emerging applications have led to a wealth of newly proposed techniques. In the music information retrieval community, many studies and applications have concentrated on tag-based music recommendation. The limitation of music emotion tags is the ambiguity caused by a single music tag covering too many subcategories. To overcome this, multiple tags can be used simultaneously to specify music clips more precisely. In this paper, we propose a novel technique to rank the proper tag combinations based on the acoustic similarity of music clips.

• Annual Conference of KIPS
• /
• 2016.10a
• /
• pp.8-9
• /
• 2016

본 연구는 Lego Mindstorms NXT 상에서 음악을 재생할 수 있도록 하는 SimMusic language를 정의한다. 재생하고자 하는 악보는 SimMusic language로 작성되고, Lego Mindstorms NXT로 조립된 SimMusic player는 SimMusic 프로그램을 읽고 음악을 재생한다. SimMusic player를 통해 하나의 악보가 재생되는 일련의 과정은 컴퓨터 구조에서 프로그램이 수행되는 과정을 기반으로 구현되었기 때문에, 본 연구는 비전공자도 쉽게 컴퓨터 과학의 기초를 다질 수 있는 계기가 된다.

• Journal of the Semiconductor & Display Technology
• /
• v.20 no.1
• /
• pp.18-24
• /
• 2021

The current settlement and distribution used in theme, background and signal music market other than conventional music is being carried out with either the comprehensive settlement method or the measured meter-rate settlement method in the payment process of collected user fees and compensation depending on the use-permission types. In this settlement and distribution process, however, the reliability issues are often being raised because of the difficulty of tracking rights due to changes in music source rights management information, etc, and the opaque settlement and distribution method itself. This paper proposes a new settlement and distribution platform using a blockchain for the reliable collection and distribution of copyright fees among music user group, monitoring organization group, trust organization group and copyright holders, based on the monitoring information of the theme, background and signal music usage. This platform also provides the transparency in settlement and distribution process among stakeholders through smart contract system.

• International Journal of Computer Science & Network Security
• /
• v.21 no.12
• /
• pp.300-308
• /
• 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 Web Engineering
• /
• v.21 no.4
• /
• pp.1265-1282
• /
• 2022

The theme, background, and signal music usage history information consists of general information such as music information, platform information, and music usage information, and sensitive information such as rights management information, music usage permission range, and contract information. If sensitive information among these is disclosed, disputes such as trade secrets and infringement of personal information protection between companies or between companies and individuals may arise. We propose a selective encryption/decryption method to secure the confidentiality, integrity, reliability and non-repudiation of sensitive music usage history information used in the theme, background, and signal music blockchain environment. In the proposed method, a monitoring company encrypts sensitive information using a secret key for usage history information, which is combined with general information, and digitally signs it using a private key to register it in a block. A trust group can view and access the information at the time of inquiry by verifying the digital signature with the public key of the monitoring company and then can decrypt the sensitive information using the private key.

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