• Journal of Distribution Science
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• v.17 no.9
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• pp.127-131
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• 2019

Purpose - This study focuses on clues that can clearly amplify the effects of background music. Review which store environments have a direct and positive impact on consumer responses, such as purchases. Research design, data, and methodology - This study focuses on clues that can clearly amplify the effects of background music. The purpose of this study is to examine what kind of store environment, combined with background music, has a direct and positive effect on consumer reactions such as purchase, and suggest future research directions. Results - The manager decides to use background music in the store because it is relatively inexpensive and easy to identify the emotional response of the consumer. In addition, appropriate background music lowers the psychological purchasing barriers of consumers. Previous studies have often not conducted a basic review of whether consumers perceive background music when it is used in retail stores. For example, it is necessary to make sure that the volume of the background music is loud enough and that the noise is properly excluded despite the congestion of the store so that the pure influence of the background music on the consumer can be measured. A way for store managers to clarify and differentiate their identity is to create a unique and satisfying store atmosphere for their customers. In order to help customers focus on their purchases, store managers must use marketing elements to integrate the five senses. And they should plan background music aiming at synergy effect of these five senses. In other words, in order to make the store atmosphere positive, it is not enough to have a suitable visual design interior or background music in the store, and consumers should have the opportunity to smell, taste and touch it directly. Conclusions - In conclusion, we hope that the following issues will be studied by several scholars in the future. It should be clarified that the impact of background music on customers varies depending on the customer's movement in the store, the selection of the background music genre order, and the timing (interval) of background music exposure to the customer.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.4
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• pp.195-200
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• 2015

Recently, most people use android based smartphones and we can find music players in any smartphones. However, it's hard to find a personalized music player which applies user's preference. In this paper, we propose an emotion-based music player, which analyses and classifies the music with user's emotion, recommends the music, applies the user's preference, and visualizes the music by color. Through the proposed music player, user could be able to select musics easily and use an optimized application.

• Journal of Digital Contents Society
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• v.18 no.3
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• pp.509-516
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• 2017

The purpose of this study is to identify the use of sound sources in music education for children, discuss how to use the digital sound sources, and explain the advantages and the disadvantages. The study participants collected data through focal group interviews with 8 preschool teachers interested in music education for children. The results of the study are as follows. Actual use of sound sources were divided into two categories: "Digital sound source is frequently used," "Need to play directly according to circumstances." The method of digital sound source use was divided into "Download as paid and provided as a cassette," "Playing sound sources directly from laptops and smartphones." Benefits and reasons for digital sound source use was divided into "Easy to use," and "Necessary when it is difficult to play the actual piece." Demerits of digital sound source use was divided into "Lacking variety" "Inconvenience of use." This study is believed to be meaningful in providing the basis for the provision of sound sources in music education for children and the basic sources of research on the use of sound sources.

• 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.27 no.11
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• pp.287-294
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• 2022

The purpose of this study is to define the concept of value-added services on online music platforms, put forward a model of users' willingness to use value-added services on online music platforms, and explore the way its influencing factors affect users' willingness to use. This study is based on the stimulus-response model, combined with the characteristics of online music service platforms, using information value, social value, and entertainment value as independent variables, using flow experience as a mediating variable, and self-awareness as a moderator variable, and then researches on the use of users. influence of will. Empirical analysis was carried out in this study using SPSS and AMOS statistical analysis tools. It is verified that the value-added services of online music platforms have a positive and positive impact on consumers' flow experience and usage intention. This research can fill in the theoretical defects of online music platform service, which has positive and important significance for music platform operators to improve their service capabilities and improve their income.

• Journal of Korea Entertainment Industry Association
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• v.15 no.1
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• pp.39-51
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• 2021

This study is based on literature review and theoretical background, we will explore the interrelationship between music and meditation and meditation image production through music, discuss the relationship between theremin instruments and musical meditation. It also describes whether the musical direction through an emotional approach meets the purpose of music meditation, focusing on the creative process and analysis of the work. In this study, the emotional aspect of music was developed, centering on the auditory characteristics of music and the inner element of meditation, to find the relationship between each other, and to prepare a specific plan for music directing to induce the inner emotion of meditation. This study deduced a way to apply music meditation with an emotional approach centering on the melody through the use of the Theremin instrument, and tried to approach the inner meaning and methodology of the work academically. It is hoped that these studies will contribute to the development of music meditation programs and the expansion of music meditation.

• Phonetics and Speech Sciences
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• v.10 no.3
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• pp.19-29
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• 2018

We propose to use independent component analysis (ICA) and deep neural network (DNN) to detect music sections in broadcast drama contents. Drama contents mainly comprise silence, noise, speech, music, and mixed (speech+music) sections. The silence section is detected by signal activity detection. To detect the music section, we train noise, speech, music, and mixed models with DNN. In computer experiments, we used the MUSAN corpus for training the acoustic model, and conducted an experiment using 3 hours' worth of Korean drama contents. As the mixed section includes music signals, it was regarded as a music section. The segmentation error rate (SER) of music section detection was observed to be 19.0%. In addition, when stereo mixed signals were separated into music signals using ICA, the SER was reduced to 11.8%.

• Journal of Multimedia Information System
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• v.4 no.3
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• pp.99-106
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• 2017

This study does a qualitative and quantitative analysis of how music by humming is being used by music educators in the classroom. Music by humming is part division of music information retrieval. In order to define what a music information retrieval system is first I need to define what it is. Berger and Lafferty (1999) define information retrieval as "someone doing a query to a retrieval system, a user begins with an information need. This need is an ideal document- perfect fit for the user, but almost certainly not present in the retrieval system's collection of documents. From this ideal document, the user selects a group of identifying terms. In the context of traditional IR, one could view this group of terms as akin to expanded query." Music Information Retrieval has its background in information systems, data mining, intelligent systems, library science, music history and music theory. Three rounds of surveys using question pro where completed. The study found that there were variances in knowledge, training and level of awareness of query by humming, music information retrieval systems. Those variance relationships where based on music specialty, level that they teach, and age of the respondents.

• Proceedings of the IEEK Conference
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• summer
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• pp.229-232
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• 2004

In this paper, we propose a robust music retrieval system based on the content analysis of music. New feature extraction method called Multi-Feature Clustering (MFC) is proposed for the robust and optimum performance of the music retrieval system. It is demonstrated that the use of MFC significantly improves the system stability of music retrieval with better classification accuracy.

• Journal of Korea Multimedia Society
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• v.16 no.4
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• pp.453-463
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• 2013

In this paper, we present an effective method and a system for the music summarization which automatically extract the chorus portion of a piece of music. A music summary technology is very useful for browsing a song or generating a sample music for an online music service. To develop the solution, conventional automatic music summarization methods use a 2-dimensional similarity matrix, statistical models, or clustering techniques. But our proposed method extracts the music summary by calculating BER(Bit Error Rate) between audio fingerprint blocks which are extracted from a song. But we could directly use an enormous audio fingerprint database which was already saved for a music retrieval solution. This shows the possibility of developing a various of new algorithms and solutions using the audio fingerprint database. In addition, experiments show that the proposed method captures the chorus of a song more effectively than a conventional method.