• Journal of Music and Human Behavior
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• v.17 no.1
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• pp.97-125
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• 2020

This case study examined the effects of synchronization-based group music therapy for improving peer interaction of children with autism spectrum disorder (ASD). The participants were five children between the ages of 6 and 10 with ASD. A total of eight 30-minute music therapy sessions were conducted two times a week. During sessions, target behaviors (i.e., engagement in joint action, synchronized movements, eye contact, and initiation of social interaction) were observed and analyzed. Also, the PIPPS-P was completed by parents to identify behavioral changes in real-life environments from pretest to posttest. Following the intervention, all of the participants showed increases in synchronized movements with peers and attempts to initiate social interaction. In addition, parents rated their children's play behavior as being improved in their everyday living environment. These results support that synchronous movements between children with ASD, which were facilitated with rhythmic cueing, led to enhanced engagement in joint action. Considering that those movements are the basis for further social skills (e.g., play behavior), this study also indicates that synchronization-based group music therapy could be an effective therapeutic approach for improving the peer interaction of this population.

• 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.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.1
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• pp.41-46
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• 2010

In this paper, the DoA(Direction of Arrival) estimator using unitary MUSIC algorithm is studied. The complex-valued correlation matrix of MUSIC algorithm is transformed to the real-valued one using unitary transform for easy implementation. The eigenvalue and eigenvector are obtained by the combined Jacobi-CORDIC algorithm. CORDIC algorithm can be implemented by only ADD and SHIFT operations and MUSIC spectrum computed by 256 point DFT algorithm. Results of unitary MUSIC algorithm designed by System Generator for FPGA implementation is entirely consistent with Matlab results. Its performance is evaluated through hardware co-simulation and resource estimation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2A
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• pp.119-127
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• 2012

In this paper a super-resolution time delay estimation algorithm is developed for real-time locating systems (RTLSs) that employ a direct-sequence spread spectrum technique, along with its performance analysis in multipath environments. The classical correlation method provides relatively good performance in line-of-sight (LOS) environments but its performance seriously degrades in multipath environments, especially when signals are spaced closer than a PN chip. Therefore we shall develop a super-resolution time delay estimation algorithm that may estimate the time delays of multipath signals even in closely spaced multipath environments using the MUSIC algorithm for direction-of-arrival estimation and analyze its performance by applying the algorithm to the ISO/IEC 24730-2.1 RTLS system. 

• Journal of Music and Human Behavior
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• v.20 no.2
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• pp.89-113
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• 2023

This study aimed to assess the feasibility and impact of a 5-week parent-led home-based music program for parents of children with autism spectrum disorder (ASD). The program aimed to enhance the parents' sense of competence and their relationships with their child. Each week for 5 weeks, 10 parents of 10 children with ASD (aged 3 to 9 years) received weekly 30-minute personalized lessons on how to implement the home-based music program and implemented the educated music program at home with activities involving receptive and active engagement. On average, the parents conducted the music program 2.5 times a week for about 9.2 minutes per session. At the end of the 5 weeks, parents reported increased comfort and effectiveness in interacting with their child through music. In addition, positive changes were noted on the Parenting Sense of Competence Scale and the closeness aspect of the parent-child relationship. Participants affirmed the program's feasibility, emphasizing its potential for supporting families with children with ASD. These results provide foundational data for future home-based music activities and programs, emphasizing the importance of tailoring interventions to the unique needs of families with children with ASD.

• The Journal of the Acoustical Society of Korea
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• v.39 no.4
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• pp.286-291
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• 2020

In this paper, we propose a system that recommends music through tempo-oriented music classification and sensor-based human activity recognition. The proposed method indexes music files using tempo-oriented music classification and recommends suitable music according to the recognized user's activity. For accurate music classification, a dynamic classification based on a modulation spectrum and a sequence classification based on a Mel-spectrogram are used in combination. In addition, simple accelerometer and gyroscope sensor data of the smartphone are applied to deep spiking neural networks to improve activity recognition performance. Finally, music recommendation is performed through a mapping table considering the relationship between the recognized activity and the indexed music file. The experimental results show that the proposed system is suitable for use in any practical mobile device with a music player.

• Phonetics and Speech Sciences
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• v.4 no.3
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• pp.103-110
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• 2012

In this paper, a target signal detection method using multiple signal classification (MUSIC) algorithm is proposed. The MUSIC algorithm is a subspace-based direction of arrival (DOA) estimation method. Using the inverse of the eigenvalue-weighted eigen spectra, the algorithm detects the DOAs of multiple sources. To apply the algorithm in target signal detection for GSC-based beamforming, we utilize its spectral response for the DOA of the target source in noisy conditions. The performance of the proposed target signal detection method is compared with those of the normalized cross-correlation (NCC), the fixed beamforming, and the power ratio method. Experimental results show that the proposed algorithm significantly outperforms the conventional ones in receiver operating characteristics (ROC) curves.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.7
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• pp.1025-1035
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• 1995

In this paper, we realize a real time digital FM synthesizer based on genetic algorithm using a general purpose digital signal processor. Especially, we synthesize diverse music sounds nicely using a synthesis model consisting of a single modulator and multiple carriers. Also we present genetic algorithm-based technique which determines optimal parameters for reconstruction through FM synthesis of a sound after analyzing the spectrum of PCM data as a standard music sound using FFT. Using the suggested parameter extractiuon algorithm, we extract parameters of several instruments and then synthesize digital FM sounds. To verify the validity of the parameter extraction algorithm as well as realization of a real time digital music synthesizer, the evaluation is first done by listening the sound directly as subjective test. Secondly, to evaluate the synthesized sound objectively with an engineering sense, we compare the synthesized sound with an original one in a time domain and a frequency domain.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1213-1228
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• 2017

The pitch tracking of music has been researched for several decades. Several possible improvements are available for creating a good t-distribution, using the instantaneous robust algorithm for pitch tracking framework to perfectly detect pitch. This article shows how to detect the pitch of music utilizing an improved detection method which applies a statistical method; this approach uses a pitch track, or a sequence of frequency bin numbers. This sequence is used to create an index that offers useful features for comparing similar songs. The pitch frequency spectrum is extracted using a modified instantaneous robust algorithm for pitch tracking (IRAPT) as a base combined with the statistical method. The pitch detection algorithm was implemented, and the percentage of performance matching in Thai classical music was assessed in order to test the accuracy of the algorithm. We used the longest common subsequence to compare the similarities in pitch sequence alignments in the music. The experimental results of this research show that the accuracy of retrieval of Thai classical music using the t-distribution of instantaneous robust algorithm for pitch tracking (t-IRAPT) is 99.01%, and is in the top five ranking, with the shortest query sample being five seconds long.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.724-726
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• 1999

We have developed a real time musical visualizing system works on PC with sound card and windows 95 or more. The system can extract some features of music signal and animate various screen -i.e wave, spectrum, simulated water jet - according to extracted features. We have used the system at the concert for the deaf and contributed for deaf to understand the music.