• Journal of Music and Human Behavior
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• v.11 no.1
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• pp.21-37
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• 2014

The significant role of joint attention in the development of children with autism spectrum disorder (ASD) has highlighted the importance of early intervention. With the emphasis on the effective cueing and reinforcer for orienting to social stimuli in improving responding to joint attention (RJA) of children with ASD, the use of musical cue was hypothesized. This study aimed to examine the occurrence of RJA behaviors depending on the attentional cue, which differed in the level of information and type of auditory modality. Nine children with ASD participated in this study. The use of eight different joint attention cues were analyzed in terms of the frequency and accuracy of RJA behaviors elicited. The results of the study showed that RJA behaviors occurred more frequently with musical cues than with verbal cues and the mean accuracy rate of RJA was higher with musical cues (p = .047). Musically delivered eliciting and directing cues accompanied with pointing elicited the highest attentional shift and RJA accuracy. The significant increases in RJA with the use of musical cues indicated that incorporating musical elements into an attentional cue may provide more accurate cue information, enough to improve RJA behaviors of children with autism.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.4 s.95
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• pp.427-437
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• 2005

In this paper, the perceived audio level metering algorithm of digital audio sound to be able to operate in real-time is proposed. Through analyzing a conventional recommendation ITU-RBS1387-I for objective audio quality analysis, FFT-based loudness metering algorithm is implemented and the real-time method of that algorithm was advised and proved. The proposed method is based on look-up table. In order to prove the proved method, using 23 pure tones and 30 preselected digital audio samples, its performance and operation time is evaluated. Its performance, compared with an original algorithm's, have a good figure of less than $2\;\%$ error even if look-up table related with spectral spreading have large level resolution of $10\;\cal{dB}$. The proposed algorithm take only 1/21 of original algorithm's measuring time. Also, in the proposed algorithm auditory pitch group energy calculation take 1/450 of original algorithm's and excitation calculation take 1/3.57. In conclusion, the proposed algorithm is expected to be implemented into DSP-based real-time loudness meter.