• The Journal of the Acoustical Society of Korea
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• v.37 no.3
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• pp.147-155
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• 2018

In this paper, we tried to find out sound quality metrics to express discomfort of overload excavator noise and to develop sound quality indexes through multiple regression analysis by using them. For this purpose, the interior noise of cabin under overload condition was recorded for six excavator models with different noise properties and Jury test was carried out by PCM (Paired Comparison Method) and MEM (Magnitude Estimation Method). Jury test result with low consistency was classified into two groups with different preference tendencies by cluster analysis and multiple regression analysis was conducted in order to find out which sound quality metrics have significant effects on discomfort(low preference). As a result, we figured out that the sound quality metrics to express the discomfort were the partial loudness (= $PN_{10Bark}$) between 0 and 10 Bark in case of group1 and the difference between engine noise(= $dB_{EG}$) and hydraulic system noise ($dB_1$) in case of group2. Using the results of preference ranking and tendency analysis of PCM followed by the correlation analysis between PCM and MEM, the more reliable results were adopted by excluding the data with low consistency obtained from Jury test via MEM.

• The Journal of the Acoustical Society of Korea
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• v.29 no.4
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• pp.258-264
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• 2010

In this paper, we propose an objective quality feature which is based on the human auditory system to measure vacuum cleaner noise. It is observed that some frequency bands are more sensitive to the human auditory system. Therefore, we divided the audible frequency range of vacuum cleaner noise into a number of frequency bands and the average energy of these bands was calculated. Among a number of average energies, an average energy of a frequency band was selected as the proposed feature. In order to test the performance of the proposed feature, fourteen vacuum cleaners were chosen and the noise was recorded in an anechoic-chamber. Then we performed subjective tests to obtain subjective scores of the noise data using the PCM (paired comparison method) and ACR (absolute category rating) subjective methods. The proposed objective quality feature shows high correlation with the subjective scores.