• Journal of Broadcast Engineering
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• v.9 no.1
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• pp.2-7
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• 2004

In this paper, we proposed the content-based music information retrieval technique using some MPEG-7 low-level descriptors. Especially, pitch information and timbral features can be applied in music genre classification, music retrieval, or QBH(Query By Humming) because these can be modeling the stochasticpattern or timbral information of music signal. In this work, we restricted the music domain as O.S.T of movie or soap opera to apply broadcasting system. That is, the user can retrievalthe information of the unknown music using only an audio clip with a few seconds extracted from video content when background music sound greeted user's ear. We proposed the audio feature set organized by MPEG-7 descriptors and distance function by vector distance or ratio computation. Thus, we observed that the feature set organized by pitch information is superior to timbral spectral feature set and IFCR(Intra-Feature Component Ratio) is better than ED(Euclidean Distance) as a vector distance function. To evaluate music recognition, k-NN is used as a classifier

• The Journal of the Korea Contents Association
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• v.14 no.12
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• pp.924-934
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• 2014

In the last 10 years the digital music contents market has grown rapidly. However digital music contents product and services are not managed with product planning and price policy considered customer attitude and digital music contents values. This study is to define the value properties of digital music contents services based on streaming and download as genre, price, sound quality, and usage appliance, and suggest the strategic market price and service composition of digital music contents service by customer attitudes about the value properties. The research used the conjoint analysis methodology based on the hedonic price model and collected 405 questionaries by users of Korean digital music contents services to the analysis. Hence 'sound quality' in download platform, and 'appliance' in streaming platform were the elements to evaluate the customer attitude. The results present the music contents productions and companies have to provide the differentiated services and price by the value properties of user preference in the market.

• Journal of Music and Human Behavior
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• v.20 no.2
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• pp.89-113
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• 2023

This study aimed to assess the feasibility and impact of a 5-week parent-led home-based music program for parents of children with autism spectrum disorder (ASD). The program aimed to enhance the parents' sense of competence and their relationships with their child. Each week for 5 weeks, 10 parents of 10 children with ASD (aged 3 to 9 years) received weekly 30-minute personalized lessons on how to implement the home-based music program and implemented the educated music program at home with activities involving receptive and active engagement. On average, the parents conducted the music program 2.5 times a week for about 9.2 minutes per session. At the end of the 5 weeks, parents reported increased comfort and effectiveness in interacting with their child through music. In addition, positive changes were noted on the Parenting Sense of Competence Scale and the closeness aspect of the parent-child relationship. Participants affirmed the program's feasibility, emphasizing its potential for supporting families with children with ASD. These results provide foundational data for future home-based music activities and programs, emphasizing the importance of tailoring interventions to the unique needs of families with children with ASD.

• Journal of the Korea Society of Computer and Information
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• v.16 no.6
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• pp.79-88
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• 2011

In this paper, We propose real-time sound editing and playback systems which is based on Augmented Reality. The proposed system are composed with music maker which is based on AR maker and music board. By using music marker's contents, the proposed system selects the kinds of musical instruments and pre-defined midi track and by calculating the relative location of music marker on 2-dimensional plane, we set the spatial relative parameter in midi track. For performance evaluation, we check the jitter value of in various resolutions by using CAM which supports $1600{\pm}1200$ as the maximum resolution. As a result, when we set the configuration value of CAM as $860{\pm}600$ pixels and process two frames per minute, the success ratio of recognizing music markers and jitter values are accegnable. It can be utilized in the fields of alternative cmacine which is based on music and also be utilized in the educational aspects because child or elderly who don't know enough musical theory can easily handle it.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.217-225
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• 2023

The willingness of online music users to pay is the key to the protection of music copyright and the sustainable development of the industry. This paper aims to study the influencing factors of online music users' willingness to pay based on exploratory analysis. Based on the theory of customer perceived value, the unified theory of technology acceptance and use, and the theory of fan enthusiasm, the research model is constructed. Validate the obtained 583 valid data. Through analysis, I got that perceived value, interpersonal influence, fan enthusiasm, and personal payment awareness directly affect online music users' willingness to pay; practical value and hedonic value have a positive impact on perceived value, and the impact of economic cost and compilation cost has not reached a significant level; Online word-of-mouth negatively moderates the impact of perceived value on users' willingness to pay for music. Music platforms can formulate operating policies based on this.

• Journal of KIISE:Databases
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• v.34 no.4
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• pp.283-303
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• 2007

Recently, the study of efficient way to store and retrieve enormous music data is becoming the one of important issues in the multimedia database. Most general method of MIR (Music Information Retrieval) includes a text-based approach using text information to search a desired music. However, if users did not remember the keyword about the music, it can not give them correct answers. Moreover, since these types of systems are implemented only for exact matching between the query and music data, it can not mine any information on similar music data. Thus, these systems are inappropriate to achieve similarity matching of music data. In order to solve the problem, we propose an Efficient Query-By-Humming System (EQBHS) with a content-based indexing method that efficiently retrieve and store music when a user inquires with his incorrect humming. For the purpose of accelerating query processing in EQBHS, we design indices for significant melodies, which are 1) frequent melodies occurring many times in a single music, on the assumption that users are to hum what they can easily remember and 2) melodies partitioned by rests. In addition, we propose an error tolerated mapping method from a note to a character to make searching efficient, and the frequent melody extraction algorithm. We verified the assumption for frequent melodies by making up questions and compared the performance of the proposed EQBHS with N-gram by executing various experiments with a number of music data.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.116-124
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• 2020

The advantage of the distance learning universities based on the 4th Industrial Revolution is that anyone can conveniently take lectures anytime, anywhere on the web. In addition, research has been actively conducted on the effect of light color and temperature control upon student performance during online classes. However, research on how the conditions of subjects, lighting colors, and music selection improve the degree of a student's concentration during online lectures has not been completed. To solve these problems in this paper, we have developed automatic analysis system SW for the weak subjects of learners by applying intelligent analysis algorithm, have proposed and simulated music therapy and art therapy. Moreover, It proposed in this paper an algorithm for an automatic analysis system, which shows the weak subjects of learners by adopting intelligence analysis algorithms. We also have presented and simulated a music therapy and art therapy algorithms, based on the blended learning, in order to increase students concentration during lecture.

• Journal of Korea Multimedia Society
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• v.23 no.6
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• pp.765-771
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• 2020

To enable AI(artificial intelligence) to realize visual emotions, it attempts to create music centered on color, an element that causes emotions in paintings. Traditional image-based music production studies have a limitation in playing notes that are unrelated to the picture because of the absence of musical elements. In this paper, we propose a new algorithm to set the group of music through the average color of the picture, and to produce music after adding diatonic code progression and deleting sound using median value. And the results obtained through the proposed algorithm were analyzed.

• ETRI Journal
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• v.38 no.3
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• pp.510-517
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• 2016

Recent developments in the field of separation of mixed signals into music/voice components have attracted the attention of many researchers. Recently, iterative kernel back-fitting, also known as kernel additive modeling, was proposed to achieve good results for music/voice separation. To obtain minimum mean square error (MMSE) estimates of short-time Fourier transforms of sources, generalized spatial Wiener filtering (GW) is typically used. In this paper, we propose an advanced music/voice separation method that utilizes a generalized weighted ${\beta}$-order MMSE estimation (WbE) based on iterative kernel back-fitting (KBF). In the proposed method, WbE is used for the step of mixed music signal separation, while KBF permits kernel spectrogram model fitting at each iteration. Experimental results show that the proposed method achieves better separation performance than GW and existing Bayesian estimators.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.1
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• pp.7-13
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• 2020

As a countermeasure against the threat of jamming which can disrupt operation of the Global Positioning System (GPS) receivers, various kinds of technique to estimate the Direction-Of-Arrivals (DOAs) of incoming jamming signals have been widely studied, and among them, the MUltiple SIgnal Classification (MUSIC) algorithm is known to provide very high resolution. However, since the previous studies regarding the MUSIC algorithm does not consider the orientation of each antenna element of antenna arrays, there is a possibility that DOA estimation performance degrades in the case of a misaligned antenna array whose antenna elements are not oriented along the same direction. As an effort to solve this problem, there exists a previous work which presents an MUSIC-based method for DOA estimation. However, the error between the real and measured values of each antenna orientation is not taken into consideration. Therefore, in this paper, the effect of the aforementioned error on the DOA estimation performance in the case of a misaligned antenna array is analyzed by simulations.