• The KIPS Transactions:PartD
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• v.10D no.3
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• pp.547-558
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• 2003

From the viewpoint of that music melody has the similar features to time-series data, music melody is transformed to a time-series data with normalization and corrections and the similarity between melodies is defined as the Euclidean distance between the transformed time-series data. Then, based the similarity between melodies of a music object, melodies are clustered and the representative of each cluster is extracted as one of theme melodies for the music. To construct the theme melody index, a theme melody is represented as a point of the multidimensional metric space of M-tree. For retrieval of user's query melody, the query melody is also transformed into a time-series data by the same way of indexing phase. To retrieve the similar melodies to the query melody given by user from the theme melody index the range query search algorithm is used. By the implementation of the prototype system using the proposed theme melody index we show the effectiveness of the proposed methods.

• Journal of Music and Human Behavior
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• v.10 no.1
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• pp.67-83
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• 2013

Assessment in music therapy is a vital part for both the therapist and client in the process of therapy. Based on what is assessed, objectives are identified to formulate specific action procedures and strategies. The existing assessment tools involve lists of skills and behaviors in developmental domains without the music assessment protocol. In this study, the authors attempted to develop an assessment protocol using rhythm production for assessing skills in cognitive and emotional-behavior domain, namely Music Therapy Assessment for Cognitive and Emotional Behaviors (MACEB). The test items of the MACEB-Rhythm were developed using rhythmic patterns varying in terms of item difficulty, which are based on the various degree of clarity in the grouping/gestalt, saliency in part-whole relationship, and complexity in repetition vs. variability. Also the developed tool purported to examine one's level of emotional behavior trait by analyzing performance of musical parameters such as tempo, pacing, and loudness in the reproduced output. In order to verify the logical sequencing of test items, firstly 61 subjects participated in verifying the item difficulty for the selected 15 pilot items. The test items were revised and re-sequenced based on the gathered scores of item difficulty. In the second procedure, seven experts in the fields of music education, music therapy and music psychology whose research interest lie in music cognition revised the developed rhythm protocol items focusing on learning sequence, cognitive process and feasibility for skills assessment. The study attempted to provide foundations for using rhythm as an assessment protocol prior to its verification of assessment validity and reliability.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.6
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• pp.239-248
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• 2018

Many new technologies are studied with the arrival of the 4th industrial revolution. In particular, emotional intelligence is one of the popular issues. Researchers are focused on emotional analysis studies for music services, based on artificial intelligence and pattern recognition. However, they do not consider how we recommend proper music according to the specific emotion of the user. This is the practical issue for music-related IoT applications. Thus, in this paper, we propose an probability-based music emotion classification technique that makes it possible to classify music with high precision based on the range of emotion, when developing music related services. For user emotion recognition, one of the popular emotional model, Russell model, is referenced. For the features of music, the average amplitude, peak-average, the number of wavelength, average wavelength, and beats per minute were extracted. Multiple regressions were derived using regression analysis based on the collected data, and probability-based emotion classification was carried out. In our 2 different experiments, the emotion matching rate shows 70.94% and 86.21% by the proposed technique, and 66.83% and 76.85% by the survey participants. From the experiment, the proposed technique generates improved results for music classification.

• Journal of Music and Human Behavior
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• v.1 no.1
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• pp.11-32
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• 2004

According to Edwin Gordon(1987, 1997, 2003), music aptitude is a product of interaction of innate potential and early environmental experiences. He referred to music aptitude of children up to nine years of age as developmental music aptitude which fluctuates due to musical environment. Music aptitude stabilizes at age nine, and the music aptitude after age nine is called "stabilized music aptitude". This research is to examine Gorden's hypothesis that the younger a child receives music education, the higher music aptitude. Also, this research is to experiment the effect of Audiation activities developed in Audie Music Curriculum on music aptitude. The researcher and another Audie teacher as a co-teacher guided children together for 30 minutes once a week. The pedagogy guidelines for informal guidance in music learning theory were kept throughout the classes. Also, Audie's teaching method which had been developed for Korean Kindergarten educational environment was also applied. Five-year-old subjects in Experimental group 1 experienced the Audie Music Curriculum of one year; five-year-old subjects in Experimental group 2 experienced it for two years. Primary Measures of Music Audiation was administered three times during their last year of Kindergarten. Subjects in the Control groups, one examined at the beginning and the other at the end of their last year in Kindergarten, received no Audie instruction. There was no significant difference in tonal aptitude, but there was significant difference in rhythmic aptitude(p< .05) among the experiemental groups. Because both Experimental groups showed statistical significance (p< .001) in the music aptitude increase during their academic years, the significant differences of the year-end music aptitude between control group and experimental groups were the expected result.

• Proceedings of the Optical Society of Korea Conference
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• 1996.09a
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• pp.20-20
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• 1996

• Fashion & Textile Research Journal
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• v.17 no.4
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• pp.524-540
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• 2015

This study develops textile pattern design ideas created through the visualization of music. Methods of auditory and synesthesia were employed to analyze various attributes of popular music genres and appoint language image, shape image, and color image to obtain their interrelationships. This study provides data that can be used to express emotional images on textile print pattern designs. This research used different genres of popular music as stimuli. The language image was extracted and introduced to the overall color scheme; in addition, the color image was verified. The analysis of the color image was executed by applying it with the color set image scale of I.R.I colors. Then, the color image of the target genre of popular music was examined and analyzed through a color tone system. The preference in shape image was realized through visual images based on basic principles of points, lines, and sides composition; subsequently, an analysis of the emotional image of popular music followed. An examination of the emotional images of different popular music genres have led to the discovery that language image, color image, and shape image all share a common emotional image. There was also a realization that similarity and interrelationship exists in language, color, and shape images experienced by listening to popular music.

• Journal of the Korean Society for information Management
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• v.19 no.3
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• pp.5-30
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• 2002

In this paper, classification feature is selected with focus of musical content, note sequences pattern, and measures similarity between note sequences followed by constructing clusters by similar note sequences, which is easier for users to search by showing the similar note sequences with the search result in the CBMR system. Experimental document was $\ulcorner$A Dictionary of Musical Themes$\lrcorner$, the index of theme bar focused on classical music and obtained kern-type file. Humdrum Toolkit version 1.0 was used as note sequences treat tool. The hierarchical clustering method is by stages focused on four-type similarity matrices by whether the note sequences segmentation or not and where the starting point is. For the measurement of the result, WACS standard is used in the case of being manual classification and in the case of the note sequences starling from any point in the note sequences, there is used common feature pattern distribution in the cluster obtained from the clustering result. According to the result, clustering with segmented feature unconnected with the starting point Is higher with distinct difference compared with clustering with non-segmented feature.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.51-60
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• 2021

Due to the growth of digital media technology, there is increasing demand of personalized education based on context data of learners throughout overall education area. For music education, several studies have been conducted for providing appropriate educational contents to learners by considering some factors such as the proficiency, the amount of practice, and their capability. In this paper, a technique has been defined to recommend the appropriate music scores to learners by extracting and analyzing the practice data and chord data. Concretely, several meaningful relationships among chords patterns and learners were analyzed and visualized by constructing the learners' profiles of proficiency, extracting the chord sequences from music scores. In addition, we showed the potential for use in personalized education by analyzing music similarity, learner's proficiency similarity, learner's proficiency of music and chord, mastered chords and chords sequence patterns. After that, the chord practice programs can be effectively generated considering various music scores using the synthetically summarized chord sequence graphs for the music scores that the learners selected.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.177-183
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• 2021

Unlike the value-oriented tendency of the older generation, the MZ generation, which is emerging as a new consumer, values individual happiness and satisfaction by recognizing consumption as a kind of play, and clearly reveals its playful characteristics compared to other generations. Therefore, this study identified users' needs for interaction elements that can give a playful stimulus to the music player UI, a key function of the music streaming app, one of the universal play activities of the MZ generation. Through previous studies, the concept and characteristics of microinteraction and gamification that can be used as play elements and the relationship between play and art as well as playful characteristics of the MZ generation were summarized. In addition, the current status was identified through case analysis of the existing music app's music player UI and user interviews were conducted through contextual inquiry methods. Afterwards, I was able to identify the positive need to apply playful elements to the music player UI through analysis of user behavior patterns, and based on this, I discovered the possibility of providing an immersive music listening experience through playful interaction.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.55-58
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• 2012

본 논문은 사용자의 각종 멀티미디어 콘텐츠 소비 히스토리를 수집하여 체계화 및 패턴 분석을 수행하고, 이를 바탕으로 사용자가 선호할 것으로 예측되는 멀티미디어 콘텐츠들을 추출하여 제공하는 콘텐츠 추천 시스템에 관한 연구이다. 본 논문에서는 콘텐츠 소비와 연관된 사용자 로그와 엔진에서 자동 추출한 사용자 그룹을 통하여 콘텐츠 추천을 수행한다. 각 사용자들의 선호정보 데이터를 분석하여 선호정보 패턴이 유사한 사용자들을 사용자 그룹으로 정의하고, 각 사용자들이 속한 사용자 그룹의 사용자 로그를 활용하여 사용자별 선호 콘텐츠를 예측한다. 본 시스템은 웹 또는 모바일 환경에서 음악, 방송, 광고, 기사 등의 방대하고 다양한 콘텐츠를 복합적으로 사용자들에게 선별하여 제공해 주며, 이들의 연관성과 사용자의 콘텐츠 선호패턴을 반영한 개인 맞춤형 콘텐츠 추천 엔진은 사용자가 선호할만한 콘텐츠들을 추천하여 사용자의 콘텐츠 소비 시의 만족도를 높여줄 수 있다.