Psychoacoustic analysis of power windows sounds: Correlation between subjective and objective evaluations

Abstract The sound quality of automotive components is becoming more and more important in the customer perception of the vehicle quality. In the present study, the sound quality of power windows was investigated through subjective and objective analyses of experimentally recorded sounds. In particular, a jury test based on Verbal Attribute Magnitude Estimation and Paired Comparison techniques was developed and presented. The combination of the two methods is a novel aspect with respect to the literature and resulted in a useful and simpler mean to obtain coherent subjective judgments. In order to quantify the power window sound quality, objective parameters were obtained applying acoustic and psychoacoustic metrics, resulting well correlated with the correspondent subjective evaluations. Additionally, correlation analyses between subjective overall (i.e. independent) judgements on sound quality and subjective dependent or objective parameters were performed. Regression analyses were applied to develop models of perceived component quality, powerfulness and annoyance. The subjective and objective quantities related to the features of loudness, sharpness and steadiness of the electric motor were found to be prominent in sound quality evaluation.

[1]  Jin Yong Jeon,et al.  Short-term noise annoyance assessment in passenger compartments of high-speed trains under sudden variation , 2015 .

[2]  Gabriella Cerrato.  Automotive Sound Quality - Accessories, BSR, and Brakes , 2009 .

[3]  J. M. Cortina,et al.  What Is Coefficient Alpha? An Examination of Theory and Applications , 1993 .

[4]  L. Thurstone.  A law of comparative judgment. , 1994 .

[5]  W. Aures,et al.  Ein Berechnungsverfahren der Rauhigkeit , 1985 .

[6]  Arne Nykänen,et al.  Specification of component sound quality applied to automobile power windows , 2009 .

[7]  Teik C. Lim,et al.  Intelligent systems approaches to product sound quality evaluations – A review , 2012 .

[8]  Seung Min Lee,et al.  Objective evaluation of human perception of automotive sound based on physiological signal of human brain , 2014 .

[9]  Emilie Poirson,et al.  A method for perceptual evaluation of products by naive subjects: Application to car engine sounds. , 2010 .

[10]  Sang-Kwon Lee,et al.  Objective evaluation of interior noise booming in a passenger car based on sound metrics and artificial neural networks. , 2009, Applied ergonomics.

[11]  D. Streiner.  Starting at the Beginning: An Introduction to Coefficient Alpha and Internal Consistency , 2003, Journal of personality assessment.

[12]  Teik C. Lim,et al.  Correlations between deficiencies in power window systems influencing sound quality and some psychoacoustic metrics , 2001 .

[13]  Yan Song Wang,et al.  A sound quality model for objective synthesis evaluation of vehicle interior noise based on artificial neural network , 2014 .

[14]  L. Cronbach.  Coefficient alpha and the internal structure of tests , 1951 .

[15]  John N. Penfold,et al.  Power Window Sound Quality - A Case Study , 1997 .

[16]  Iva Salom,et al.  Subjective evaluation and an objective measure of a church bell sound quality , 2014 .

[17]  Jin-Su Kim,et al.  Development of a sound quality index for the wash cycle process of front-loading washing machines considering the impacts of individual noise sources , 2015 .

[18]  Samir N. Y. Gerges,et al.  A sound quality-based investigation of the HVAC system noise of an automobile model , 2009 .