Abstract
Sound quality analysis basically involves using tedious subjective evaluations, which involve with the problems related to the reliability and repeatability of the evaluation data as well as the time and cost. What is needed is an objective method for predicting subjective evaluation with good accuracy. In this paper, the support vector machine (SVM) has been employed to build models for the two descriptors: annoyance and muffle of the loudness-adjusted car interior noise. The nonmetric multidimensional scaling (NMDS) and principal component analysis (PCA) have been used as data pre-processor. By comparing the results with artificial neural network (ANN) and multivariate linear regression (MLR), it is confirmed that the SVM is an effective method for the modeling in the objective evaluation.
Original language | English |
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Title of host publication | Institute of Noise Control Engineering of the USA - 35th International Congress and Exposition on Noise Control Engineering, INTER-NOISE 2006 |
Pages | 4779-4788 |
Number of pages | 10 |
Volume | 7 |
Publication status | Published - 1 Dec 2006 |
Externally published | Yes |
Event | 35th International Congress and Exposition on Noise Control Engineering - Honolulu, United States Duration: 3 Dec 2006 → 6 Dec 2006 Conference number: 35 |
Conference
Conference | 35th International Congress and Exposition on Noise Control Engineering |
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Abbreviated title | INTER-NOISE 2006 |
Country/Territory | United States |
City | Honolulu |
Period | 3/12/06 → 6/12/06 |