• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.1
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• pp.84-89
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• 2011

Musical sheet recognition is an emerging area as the role of computers in music increases. Although there are several well-known programs for composition, they have a limitation in that they cannot edit or play music generated from other programs. In this paper, we propose an algorithm that can read, recognize, and play music using printed sheets. The proposed algorithm first removes lines using horizontal histogram and extracts symbols. The symbols belong to one of the three categories; notes, rests, and other signs. Notes are recognized using the context information and rests and signs are recognized using a fuzzy ART algorithm. The proposed algorithm were applied to 50 pages of musical sheets and the experimental results showed that it is effective in automatic recognition of musical sheets.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.5
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• pp.299-307
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• 2022

Harmony Search (HS) is a relatively recently developed meta-heuristic optimization algorithm, and various studies have been conducted on it. HS is based on the musician's improvisational performance, and the objective variables play the role of the instrument. However, each instrument is given only a sound range, and there is no concept of a scale that can be said to be the basis of music. In this study, the performance of the algorithm is improved by introducing a scale to the existing HS and quantizing the bandwidth. The introduced scale was applied to HM initialization instead of the existing method that was randomly initialized in the sound band. The quantization step can be set arbitrarily, and through this, a relatively large bandwidth is used at the beginning of the algorithm to improve the exploration of the algorithm, and a small bandwidth is used to improve the exploitation in the second half. Through the introduction of scale and bandwidth quantization, it was possible to reduce the algorithm performance deviation due to the initial value and improve the algorithm convergence speed and success rate compared to the existing HS. The results of this study were confirmed by comparing examples of optimization values for various functions with the conventional method. Specific comparative values were described in the simulation.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.3
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• pp.607-612
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• 2019

In this paper, we measured and analyzed the EEG signals related to the relativity between musical stimuli and human concentration for memorization. In our experiments, the subjects carried out the tasks related to human memorization exposing to musical stimuli and the tasks are to memorize the english words. We used two kinds of musical stimuli, one is a sedative tendency music and the other is a stimulative tendency music. We presented the results that are analyzed as the EEG signals by frequency bands, respectively.

• Journal of Electrical Engineering and Technology
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• v.8 no.2
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• pp.288-294
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• 2013

The diagnosis of motor failures using an on-line method has been the aim of many researchers and studies. Several spectral analysis techniques have been developed and are used to facilitate on-line diagnosis methods in industry. This paper discusses the first application of a motor flux spectral analysis to the identification of broken rotor bar (BRB) faults in induction motors using a multiple signal classification (MUSIC) technique as an on-line diagnosis method. The proposed method measures the leakage flux in the radial direction using a radial flux sensor which is designed as a search coil and is installed between stator slots. The MUSIC technique, which requires fewer number of data samples and has a higher detection accuracy than the traditional fast Fourier transform (FFT) method, then calculates the motor load condition and extracts any abnormal signals related to motor failures in order to identify BRB faults. Experimental results clearly demonstrate that the proposed method is a promising candidate for an on-line diagnosis method to detect motor failures.

• The Journal of the Acoustical Society of Korea
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• v.38 no.6
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• pp.716-723
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• 2019

Fingerprint matching accuracy is essential in deploying a music search service. This paper deals with a method to improve fingerprint matching accuracy by utilizing an auxiliary information which is called power weight. Power weight is an expected robustness of each hash bit. While the previous power mask binarizes the expected robustness into strong and weak bits, the proposed method utilizes a real-valued function of the expected robustness as weights for fingerprint matching. As a countermeasure to the increased storage cost, we propose a compression method for the power weight which has strong temporal correlation. Experiments on the publicly-available music datasets confirmed that the proposed power weight is effective in improving fingerprint matching performance.

• 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.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.3-6
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• 1988

The UCERSS algorithm is an extended MUSIC which is used to estimate incident angles of multiple wide band signals. The purpose of this paper is to extend the UCERSS in order to estimate the direction of arrivals of multiple wide band signals in multipath environment. The modifications of the UCERSS result in the wide band spatial smoothing and the UNSS approaches. Computer simulation results indicate that the performances of the UNSS are superior to those of the UCERSS and the wide band spatial smoothing method.

• Journal of Music and Human Behavior
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• v.13 no.1
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• pp.61-87
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• 2016

With broad individual variability in social communication skills of children with autism spectrum disorders and increasing focus on interventions targeting social communication of this population, there is a need for systematic analysis of how social communication outcomes are measured. This study aimed to systematically analyze the measurement tools used in the music therapy interventions for improving social communication of children with ASD. Electronic databases and music therapy journals were searched for controlled studies published between 1980 and 2015. A total of 21 studies were included for the analysis. The results demonstrated that direct observation of behaviors was the most frequently used and the combination of targeted social communication areas and specific measurements used for a specific skill varied among the studies. In addition, 90.4% of studies reported interrater reliability. These results indicate that there has been a diversity in approaches to measure social communication skills despite increasing attempts for systematic measurements. In consideration of the nature of social communication development in children with ASD, multifaceted strategy to understand and assess the target skills in terms of specific behavior acquisition, social functioning in general, and social cognition was recommended.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.239-246
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• 2023

In this paper, we propose an open-loop algorithm to classify speech and music signals using the spectral flux parameters and Mel Frequency Cepstral Coefficients(MFCC) parameters for the audio coder. To increase responsiveness, the MFCC was used as a short-term feature parameter and spectral fluxes were used as a long-term feature parameters to improve accuracy. The overall voice/music signal classification decision is made by combining the short-term classification method and the long-term classification method. The Gaussian Mixed Model (GMM) was used for pattern recognition and the optimal GMM parameters were extracted using the Expectation Maximization (EM) algorithm. The proposed long-term and short-term combined speech/music signal classification method showed an average classification error rate of 1.5% on various audio sound sources, and improved the classification error rate by 0.9% compared to the short-term single classification method and 0.6% compared to the long-term single classification method. The proposed speech/music signal classification method was able to improve the classification error rate performance by 9.1% in percussion music signals with attacks and 5.8% in voice signals compared to the Unified Speech Audio Coding (USAC) audio classification method.

• Proceedings of the KAIS Fall Conference
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• 2010.11b
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• pp.535-538
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• 2010

컴퓨터로 대변되는 과학기술의 빠른 발전은 창조적인 음악 생산에 있어서 그 궤(軌)를 같이 한다. 오랫동안 전통적으로 사용되었던 음악 창작 방식은 최근의 50여 년 동안의 과학발전에 기인하여 그 방식이 빠르게 변화하였다. 현재의 많은 음악 창작가들은 컴퓨터와 MIDI의 등장으로 보다 빠르고 편리하게 자신들의 음악 창작물을 생산할 수 있게 되었다. 하지만 현재에도 꾸준히 개발되고 있는 전자 장비들은 단순히 음악 창작 활동의 도구일 뿐이다. 음악 작업에서의 이러한 장비들의 사용은 작곡가를 포함한 음악 생산자의 창의성이 전제 되어야 하는 것은 자명한 일이다. 본 논문은 Karlheinz Stockhausen을 위시한 여러 전자 음악가들의 작품을 분석하여 새로운 방식의 음악 창작을 연구하고, 그것을 토대로 다양하면서도 새로운 형태의 음악을 생산하고자 함이다.