• 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 Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.4
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• pp.275-280
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• 2015

In this paper, we studied for modified MUSIC algorithm of direction of arrival (DOA)estimation. Modified MUSIC algorithm search optimal covariance matrix using singular value decomposition and Bayes method, and desired signals are estimated by updating weight. In order to estimation of desired signals, we used sub spatial method of MUSIC algorithm. General MUSIC algorithm can estimate a desired signal in case of non-correlation signal. But, general MUSIC algorithm in case of correlation signal can not estimate a desired signals and resolution is decreased. Though simulation in case of correlation signal, we analyze to compare proposed MUSIC algorithm with general MUSIC algorithm.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.419-420
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• 2007

In this method, we extract peak periods using energy contents of each segment of music. This feature extraction method is equally applied on both the training and query music. Similarity matching algorithm is applied on the extracted feature values for identifying the query music from the database. The retrieval accuracy of 95% of our method is a pretty good result.

• Asia pacific journal of information systems
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• v.25 no.1
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• pp.119-141
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• 2015

With the rapid spread of social media, video-sharing social media like YouTube has emerged as a consumption and distribution channel for entertainment goods such as music videos and movie trailers. In tourism research, there has been a lot of research of how the visual media such as movies and soap operas induced tourism. However, no studies have attempted to examine the role of social media as a music consumption channel and its impact on tourism. Expanding a body of media-induced tourism, we analysed the impact of video-sharing social media on music-induced tourism with a case of Korean pop music and inbound tourism to Korea. Developing a Web-crawler, we collected YouTube users' comments data on 166 Korean pop music video clips which were released from 2009 to 2012 with over 1 million view counts. Controlling many of the determinants of tourism and analysing country-by-country impact of YouTube comments with the panel data, we found that engagement of Korean pop music video clips on YouTube is a significant predictor for the flow of inbound tourists to Korea.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.239-245
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• 2020

The Ewha Music Database (EMDB) is an online database comprised of primary source materials related to music education from East Asia during the modern era (1880 to 1945) when Korea, Japan, and China were geopolitically and culturally intertwined. We developed the incipit search in EMDB as an embedded tool. This is the first attempt in Korea to implement a unique search function of musical data using alphabets of musical notes. Unlike in traditional search system that uses general literature information search conditions, such as author, title, publisher, year, number of pages, etc., it offers a new way of searching a musical piece/work and sheet music. This study confirms that digital information technology is an important methodology for research of music culture as a field of humanities.

• Journal of Korean Library and Information Science Society
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• v.41 no.3
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• pp.205-224
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• 2010

The purpose of this study aims to present the base for the rational management of printed music as an important primary source of music materials. In this study, therefore, the selection and acquisition, organization, user services for the management of printed music are investigated. Then the present situation for management of printed music of university libraries in Daejeon and Chungnam are surveyed. Finally, the special issues to be considered in the management of printed music are presented.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1341-1350
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• 2000

Much research has been performed to represent music information on computers. However, one problem of the previous approaches is that music information cannot be hared with other music systems since they have used their own representation schemes. In order to resolve this problem, we have developed a new scheme for representing, editing, and playing rhythms among music information based on XML which is a web standard language. We present a RDML (Rhythm Description Markup Language) to exactly describe rhythm information such as beats, musical instruments, and performance information, which is much simpler thant previous representation schemes. Moreover, the RDML representation can be played by converting it into SMIL representation. Because our approach is based on the web standard, the music information can be shared on the web.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.7
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• pp.1435-1442
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• 2009

This paper proposes a music recommendation system for a driver in vehicle. The proposed system provides (selects and plays) a music to a driver in vehicle in real-time manner by inferring his preference based on physical, environmental, and personal information. Pulse data as physical information, age and biorhythm as personal information, and time as environmental information are used to infer a driver's and thus recommend a music. Experimental results showed that the proposed system could provide better satisfaction to a driver on the recommended music compared to the conventional approach.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.258-261
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• 2007

This paper presents techniques to recognize music using back propagation network, one of the neural network algorithms, and to preprocess technique for music image. Music symbols and music notes are segmented by preprocessing such as binarization, slope correction, staff line removing, etc. Segmented music symbols and music notes are recognized by music note recognizing network and non-music note recognizing network. We proved correctness of proposed music recognition algorithm through experiments and analysis with various kind of musics.

• Journal of the Korea Society of Computer and Information
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• v.13 no.3
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• pp.99-106
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• 2008

Recently, digital music retrieval is using in many fields (Web portal. audio service site etc). In existing fields, Meta data of music are used for digital music retrieval. If Meta data are not right or do not exist, it is hard to get high accurate retrieval result. Contents based information retrieval that use music itself are researched for solving upper problem. In this paper, we propose Same music recognition method using similarity measurement. Feature data of digital music are extracted from waveform of music using Simplified MFCC (Mel Frequency Cepstral Coefficient). Similarity between digital music files are measured using DTW (Dynamic time Warping) that are used in Vision and Speech recognition fields. We success all of 500 times experiment in randomly collected 1000 songs from same genre for preying of proposed same music recognition method. 500 digital music were made by mixing different compressing codec and bit-rate from 60 digital audios. We ploved that similarity measurement using DTW can recognize same music.