• Journal of Music and Human Behavior
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• v.1 no.1
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• pp.1-10
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• 2004

Being engaged in the musical tasks needs cognitive skills to perceive musical sound, organize them into meaningful unit, store them in the memory and retrieve them when needed. These skills are also required for academic tasks indicating that there is positive correlation between skills for musical and academic tasks. Based on these findings, the study purported to examine whether the developed sessions can enhance cognitive skills which is composed of auditory information skills, which is composed of perceiving sounds, organizing them into groups based on the existing information or organization pattern, and short-term memory skills. Eighteen elementary students in 4, 5, and 6th grades have participated in the study. The study has administered Music Cognitive Skills Test(MCST) before and after implementing music therapy sessions. The MCST consisted of five parts, first one measuring the rhythm imitating skills, second, measuring the melodic imitation skills, third, measuring discriminative skills in identifying higher pitch, fourth, measuring discriminative skills in identifying identical chords, and lastly, measuring the tone retention skills. The results indicated that there was statistical difference between the pre and post test in rhythm and melody imitation skills. Because reproduction of perceived rhythm patterns requires memory skills, imitating patterns are considered cognitive skills. Also melody is defined adding spatial dimension to the rhythm which is temporal concept. Being able to understand melodic pattern and to reproduce the pattern also requires cognitive skills. The subjects have shown significant improvement in these two areas. In other areas, there were definite increase of scores, however, no significant differences. The study also explores interpretation of these results and also observed consistencies among the participants in completing the musical tasks.

• Journal of Korea Entertainment Industry Association
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• v.13 no.7
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• pp.205-218
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• 2019

Music sampling, which has been popular since hip-hop DJs used it in the 1970s, is now one of methods of producing music that is used regardless of genre or country. In this study, an overall production methodology for music sampling was presented through in terms of content and techniques. First of all, in terms of the contents, we classified them into the reuse and length of materials, and the function of samples in the mixed songs. In terms of the techniques, editing and effecting techniques were classified. By combining these elements, the methodology of music sampling applicable to the productions as well as the analysis was presented. Based on this methodology, the sampled songs of Korean Popular musicians - Jang Ki-ha and Faces, Epik High, The Quiet, and DJ DOC - were successfully analysed. Through the analysis process, the organic relationship of elements within the methodology was investigated, and the results of the analysis showed the effectiveness of the proposed methodology. This study can be meaningful in laying the groundwork for applying music sampling directly when actually producing songs or analyzing sampled songs.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.5
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• pp.31-36
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• 2011

In this paper, Mel-Frequency Cepstral Coefficient (MFCC), Decorrelated Filter Bank (DFB), Octave-based Spectral Contrast (OSC), Zero-Crossing Rate (ZCR), and Spectral Contract/Roll-Off are combined as a set of multiple feature-vectors for the music genre classification system based on the Support Vector Machine (SVM) classifier. In the conventional system, feature vectors for the entire genre classes are normalized for the SVM model training and classification. However, in this paper, selected feature vectors that are compared based on the One-Against-One (OAO) SVM classifier are only used for normalization. Using OSC as a single feature-vector and the multiple feature-vectors, we obtain the genre classification rates of 60.8% and 77.4%, respectively, with the conventional normalization method. Using the proposed normalization method, we obtain the increased classification rates by 8.2% and 3.3% for OSC and the multiple feature-vectors, respectively.

• The Journal of the Acoustical Society of Korea
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• v.41 no.3
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• pp.367-374
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• 2022

In this paper, correlation analysis between speech characteristics and the dose of antipsychotic drugs was performed. To investigate the pattern of speech characteristics of ExtraPyramidal Symptoms (EPS) related to voice change, a common side effect of antipsychotic drugs, a Korean-based extrapyramidal symptom speech corpus was constructed through the sentence development. Through this, speech patterns of EPS and non-EPS groups were investigated, and in particular, a strong speech feature correlation was shown in the EPS group. In addition, it was confirmed that the type of speech sentence affects the speech feature pattern, and these results suggest the possibility of early detection of antipsychotics-induced EPS based on the speech features.

• Journal of Gifted/Talented Education
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• v.22 no.2
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• pp.221-241
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• 2012

The purpose of this study was to explore differences in styles of perfectionism, stress, and career decision-making of gifted musicians by their grade level and examine the effect of perfectionism and stress of gifted musicians on their rational career decision-making. The participants of this study were 88 gifted musicians attending in the middle school of arts. The results indicated that there were significant differences in dimensions of perfectionism by the grade level of gifted musicians. The tendency of self-oriented, other-oriented, and socially prescribed perfectionism was higher with grade level. There were significant differences by grade level in stresses that gifted musicians experienced. The higher a grade level was, the more gifted musicians got stresses in self-development, parent-child relationship, peer relationship, and school life. The effect of grade level on career decision-making was significant in the rational and the transitional career decision-making. The higher a grade level was, the more rational decision-making was but the less transitional decision-making was. Meanwhile, when the effect of perfectionism and stress of gifted musicians on the rational career decision-making was examined, the rational career decision-making was predicted by self oriented perfectionism and self-development stress.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.5
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• pp.18-27
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• 2006

Rapid increase of the amount of music data demands for a new method that allows efficient similarity retrieval of music genre using audio features in music databases. To build this similarity retrieval, an indexing techniques that support audio features as a time-series pattern and data mining technologies are needed. In this paper, we address the development of a system that retrieves similar genre music based on the indexing techniques. We first propose the structure of content-based music genre retrieval system based on the time-series pattern index file and data mining technologies. In addition, we implement the time-series pattern index file using audio features and present performance analysis of the time-series pattern index file for similar genre retrieval. The experiments are performed on real data to verify the performance of the proposed method.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.927-932
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• 2009

There is such a kind of characteristic by using the computer digitization technology's interaction. It not only provides the authoring tool, and also has the user-friendly window. The paper based on this kind of interaction, through the sound and the color exchange of information, as well as each information's digitization, carries on about the scientific dielectric related advance research. This research carries on the analysis to the people to the color and the sound perceptual characteristic first, then makes comparison to the people regarding the color and the music perceptual cognition.. The research is about the research stage of the interactive sound installation creation, which shape is carried on the analysis through the extraction image in color. It is based on the perceptual characteristic,is that the algorithm manufacture reasearch of how to make color sonification. Through capturing the non-stop changing colors by camera,it transforms colors into music. The paper's foundation is the fundamental algorithm manufacture of experimental music composition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.493-494
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• 2009

Mobile phone is becoming multi-functionality devices rather than simply communication machine devices. Now, the mobile keep the run of the PC and much technical progress has been made. Recently, the Android open mobile platform has emerged, as they unveiled the Software Developer Kit to be possible to develop on the Android open mobile platform, it could be possible directly to make innovative Application development. Therefore, in this paper, a characteristic of a mobile mobility and multi-functionality is can for everyone easily compose music by built the music compose system.

• The Journal of the Acoustical Society of Korea
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• v.38 no.3
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• pp.314-319
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• 2019

Computing chromagram similarity is indispensable in constructing cover song identification system. This paper proposes a code-based chromagram similarity to reduce the computational and the storage costs for cover song identification. By learning a song-specific codebook, a chromagram sequence is converted into a code sequence, which results in the reduction of the feature storage cost. We build a lookup table over the learned codebooks to compute chromagram similarity efficiently. Experiments on two music datasets were performed to compare the proposed code-based similarity with the conventional one in terms of cover song search accuracy, feature storage, and computational cost.

• The Journal of the Acoustical Society of Korea
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• v.28 no.5
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• pp.471-476
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• 2009

In this paper, we apply a discriminative weight training to a support vector machine (SVM) based speech/music classification for the selectable mode vocoder (SMV) of 3GPP2. In our approach, the speech/music decision rule is expressed as the SVM discriminant function by incorporating optimally weighted features of the SMV based on a minimum classification error (MCE) method which is different from the previous work in that different weights are assigned to each the feature of SMV. The performance of the proposed approach is evaluated under various conditions and yields better results compared with the conventional scheme in the SVM.