• The Journal of the Acoustical Society of Korea
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• v.34 no.3
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• pp.247-255
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• 2015

This paper presents a study on the performance of the music search based on the automatically recognized music-emotion labels. As in the other media data, such as speech, image, and video, a song can evoke certain emotions to the listeners. When people look for songs to listen, the emotions, evoked by songs, could be important points to consider. However; very little study has been done on the performance of the music-emotion labels to the music search. In this paper, we utilize the three axes of human music perception (valence, activity, tension) and the five basic emotion labels (happiness, sadness, tenderness, anger, fear) in measuring music similarity for music search. Experiments were conducted on both genre and singer datasets. The search accuracy of the proposed emotion-based music search was up to 75 % of that of the conventional feature-based music search. By combining the proposed emotion-based method with the feature-based method, we achieved up to 14 % improvement of search accuracy.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.26 no.3E
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• pp.69-73
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• 2007

This paper presents an efficient algorithm to retrieve similar music files from a large archive of digital music database. Users are able to navigate and discover new music files which sound similar to a given query music file by searching for the archive. Since most of the methods for finding similar music files from a large database requires on computing the distance between a given query music file and every music file in the database, they are very time-consuming procedures. By measuring the acoustic distance between the pre-classified music files with the same type of emotion, the proposed method significantly speeds up the search process and increases the precision in comparison with the brute-force method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.3
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• pp.192-195
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• 2008

People have tendency of forgetting music title, though they easily remember particular part of music. If a music search system can find the title through a part of melody, this will provide very convenient interface to users. In this paper, we propose an algorithm that enables this type of search using feature transformation function. The original music is transformed to new feature information with sequential melodies. When a melody that is a part of search music is given to the system, the music retrieval system searches the music similar to the feature information of the melody. Moreover, this transformation function can be easily extended to various music recognition systems.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.81-87
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• 2013

In this paper, we propose a music search algorithm for automotive infotainment system. The proposed method extracts fingerprints using the high peaks based on log-spectrum of the music signal, and the extracted music fingerprints store in cloud server applying a hash value. In the cloud server, the most similar music is retrieved by comparing the user's query music with the fingerprints stored in hash table of cloud server. To evaluate the performance of the proposed music search algorithm, we measure an accuracy of the retrieved results according to various length of the query music and measure a retrieval time according to the number of stored music database in hash table.

• The Journal of the Acoustical Society of Korea
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• v.36 no.6
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• pp.436-441
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• 2017

Computing music similarity is indispensable in constructing music retrieval system. This paper focuses on the cover song search among various music-retrieval tasks. We investigate the cover song search method based on the chroma n-gram to reduce storage for feature DB and enhance search accuracy. Specifically we propose t-tab n-gram, n-gram selection method, and n-gram set comparison method. Experiments on the widely used music dataset confirmed that the proposed method improves cover song search accuracy as well as reduces feature storage.

• The Transactions of the Korea Information Processing Society
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• v.5 no.1
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• pp.1-11
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• 1998

This paper describes design and implementation of the system that is used to efficiently retrieve music information at a digital music library. Unlike typical music information retrieval systems, this system allows the user to sing a part of the melody through the microphone which he/she wants to find rather than using title, composer or the subject catalog to search. The system then recognizes the musical notes information through the signal processing of the sounds of the entered melody, and the intervals contour is created based on this information and used as a search pattern. By running the proposed notes string search algorithm that uses the musical notes information processed with the user input, and it produces the approximate search results. Therefore, users are able to retrieve and appreciate the music whenever he/she can sing any portion of the desired music.

• The Journal of the Korea Contents Association
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• v.10 no.8
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• pp.130-137
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• 2010

An advancement and wide use of portable multimedia devices make it easy to spread digital sound source, enabling users to use portable multimedia devices and search and enjoy digital sound sources and related contents. In opposition the off-line musical service market with CD stagnates gradually and in the crisis where the off-line musical service market vanishes away. In this paper, we propose the mobile music album information retrieval system which combines the barcode and a cellular phone musical service. To get digital sound sources and related information from music albums, the proposed retrieval system uses one-dimensional barcodes attached to music albums and obtains information on related albums from the sound source servers. Also, to reflect user preferences in search results, the system uses search frequency by music album, and searches albums in music genres selected by users in the order of the recent preference. The proposed mobile music album retrieval system is implemented on the basis of WIPI, and is now providing pilot services.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.11
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• pp.880-885
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• 2017

In AD-MUSIC algorithm, DOD/DOA can be estimated without computationally expensive two-dimensional search. In this paper, to further reduce the computational complexity, the Newton type method has been applied to one-dimensional search. In this paper, we summarize the formulation of the AD-MUSIC algorithm, and present how to apply Newton-type iteration to AD-MUSIC algorithm for improvement of the accuracy of the DOD/DOA estimates. Numerical results are presented to show that the proposed scheme is efficient in the viewpoints of computational burden and estimation accuracy.

• Journal of Korea Multimedia Society
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• v.10 no.3
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• pp.391-400
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• 2007

According to the recent advances in multimedia computing, storage and searching technology have made large volume of music contents become prevalent. Also there has been increasing needs for the study on efficient categorization and searching technique for music contents management. In this paper, a new classifying method using the local information of music content and music tone feature is proposed. While the conventional classifying algorithms are based on entire information of music content, the algorithm proposed in this paper focuses on only the specific local information, which can drastically reduce the computing time without losing classifying accuracy. In order to improve the classifying accuracy, it uses a new classification feature based on music tone. The proposed method has been implemented as a part of MuSE (Music Search/Classification Engine) which was installed on various systems including commercial PDAs and PCs.