• Journal of Korea Entertainment Industry Association
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• v.14 no.3
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• pp.229-236
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• 2020

In this paper, the tone of Daegeum, one of the most representative wind instruments of our country, was analyzed. Daegeum is widely used as Jeongak Daegeum and Sanjo Daegeum, which are played in royal and wind music, and Sanjo Daegeum is mainly played in Sanjo, Sinawi and folk music. The reason why the two pieces of music are being played in different music genres is due to the improvement of the length of the pipe and the location of the finger holes, allowing the Sanjo Daegeum to perform faster than Jeongak Daegeum, apply various techniques, and make the choice of musical instruments harmonized with music by making the difference in tone. For timber analysis of Jeongak Daegeum and Sanjo Daegeum, the composition of the overtones was visually verified through Spectrogram and Spectrum Analizer, in which the results of recordings were recorded by playing octave low, flat, and octave high positions with the same power. From this, Jeongak Daegeum, which is rich in low-pitched sound, harmonizes with solemn music such as royal music, and Sanjo Daegeum, which has a relatively clear high-pitched sound, is well suited to bright music such as solo music.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.367-372
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• 2023

In this paper, we analyzed through the EEG signals how musical stimulus affects learning activities. Musical stimuli were divided into sedative and stimulative tendency music, preferred and non-preferred music, and the learning activity tasks were divided into mathematics tasks and memorization tasks. The signals measured in the EEG experiments were analyzed with the power spectrum of SMR waves known to be related to human concentration. Those spectra used for quantitative comparison in this paper. As a result the power of the EEG signals was observed to be greater than the case where music was given as a stimulus. Regardless of the type of task, the power of the EEG signals was observed to be greater in the case of sedative tendency than in the case of stimulative tendency, and the power of the EEG signals was observed to be greater in the case of favorite music than in the case of unfavorite music. From these results, it is estimated that if the musical stimulus exists, in the case of sedative tendency music, and in the case of favorite music, concentration can be increased than in the relative case.

• Journal of Music and Human Behavior
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• v.20 no.2
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• pp.61-88
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• 2023

This case study examined whether a cooperative musical instrument playing could enhance interactions between children with autism spectrum disorder (ASD) and their neurotypical (NT) siblings. It involved three children with ASD aged 7-12 years and three NT siblings aged 6-11 years. Each group, comprising a child with ASD and their NT sibling, participated in a 40-minute sessions twice weekly for eight sessions over four weeks. The intervention included three stages: simultaneous action, complementary action, and achieving a joint goal. Evaluation criteria included the initiation and response behaviors of each child, and sequential interactive behaviors and cooperative behaviors between pairs were measured. Additionally, before and after the intervention, parents and NT sibling assessed their perceived sibling relationships. Results showed increased interactive and cooperative behaviors. Post-intervention, both parents and NT siblings rated the sibling relationship highly, despite little change in sibling conflict and competition consciousness. These findings indicate that interactive instrument playing can enhance perceptions of siblings as cooperative play partners and aid in teaching them how to collaborate during interactions.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.89-94
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• 2021

In this paper, we presented the results of analysis with data obtained through EEG measurements to confirm the effect of musical stimulus when performing mathematical tasks. While the subject was solving a mathematical task, favorite and unfavorite music classified according to the subject's preference were presented as musical stimulus and the tasks were divided into memorization task and procedure task. The data measured in the EEG experiments was divided into theta waves, SMR waves and mid-beta waves which are the frequency bands related to concentration to compare the relative power spectrum values. In our results, in the case of comparing no music with favorite music and no music with unfavorite music, a significant difference was observed in the several channels, and the average difference was shown in the channels F3 and F4 of the frontal lobe. In that channels, the power was found to be greater when the music was presented than the case where there was no music. Depending on the subject's preference, it was confirmed that favorite music showed greater brain activity than unfavorite music.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.3
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• pp.515-523
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• 1997

A high resolution algorithm is presented for resolving multiple coherent spread spectrum signals that are incident on an equispaced linear array. Unlike the conventional noise-eigenvector based methods, this algorithm makes use of the signal eigenvectors of the array spectral density matrix that are associates with eigenvalues that are larger than the sensor noise level. Simulation results are shown to demonstate the high performance of the proposed approach in comparison with MUSIC in which coherent signal subspace method (CSM) is employed.

• 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.

• MALSORI
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• no.64
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• pp.89-103
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• 2007

In this paper, we introduce mel-cepstrum modulation energy (MCME) for a feature to discriminate speech and music data. MCME is a mel-cepstrum domain extension of modulation energy (ME). MCME is extracted on the time trajectory of Mel-frequency cepstral coefficients, while ME is based on the spectrum. As cepstral coefficients are mutually uncorrelated, we expect the MCME to perform better than the ME. To find out the best modulation frequency for MCME, we perform experiments with 4 Hz to 20 Hz modulation frequency. To show effectiveness of the proposed feature, MCME, we compare the discrimination accuracy with the results obtained from the ME and the cepstral flux.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.8
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• pp.12-19
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• 2017

In this paper a super-resolution time delay estimation algorithm that estimates the time delays of spread spectrum signals using sparse signal reconstruction approach is introduced. So far, the correlation method has been mostly used to estimate the time delays of spread spectrum signals. However it fails to accurately estimate the time delays in the case where the signals are spaced within approximately 1 PN chip duration and a further processing should be applied to the correlation outputs in order to enhance the resolution capability. Recently sparse signal approaches attract much interest in the area of directions-of-arrival estimation, of which SPICE is the most representative. Thus we introduce a super-resolution time delay estimation algorithm based on the SPICE approach and compare its performance with that of MUSIC algorithm by applying them to the ISO/IEC 24730-2.1 RTLS system.

• The Journal of the Acoustical Society of Korea
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• v.23 no.3
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• pp.214-220
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• 2004

A computationally efficient algorithm is presented for 3-D near-field source localization using a uniform circular away (UCA). Algebraic relations are demonstrated between the incident angles (elevation angle and azimuth angle) under the far-field assumption and the actual near-field location (range. elevation angle, and azimuth angle). Using these relations as paths to follow to the peak of the 3-D MUSIC spectrum, the proposed algorithm replaces the 3-D search required in the conventional 3-D MUSIC with a 1-D path following after a 2-D initialization. thereby reducing the computational burden.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1302-1309
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• 2014

In this paper, we propose a method to improve the performance of the direction-of-arrival (DOA) estimation of a speech source using a multiple signal classification (MUSIC)-based algorithm. Basically, the proposed algorithm utilizes a complex coefficient band pass filter to generate the narrow band signals for signal analysis. Also, reverberation component reduction and quadratic function-based response approximation in MUSIC spatial spectrum are utilized to improve the accuracy of DOA estimation. Experimental results show that the proposed method outperforms the well-known generalized cross-correlation (GCC)-based DOA estimation algorithm in the aspect of the estimation error and success rate, respectively.Abstract should be placed here. These instructions give you guidelines for preparing papers for JICCE.