• Journal of KSNVE
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• v.9 no.5
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• pp.991-997
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• 1999

It is getting higher the demand on a good sound in a car. Like some other sensory qualities, achieving a good sound is still treated as a black-box followed by the individual taste of tuning engineers. This study aims to define the attributes of a good car audio sound and the assessment factors affecting the sound quality. With a variety of surveys on professional listening groups and car audio installers, 26 most frequently used vocabularies are selected as typical presentations of car audio sound quality. After repetitions of listening tests with deliberately selected test CD, pre-recorded 15 different digital car-recordings, headphones replay system, and three different listening groups, it is proved that there are at least 5 different assessment factors which significantly affect the car audio sound quality. They are high fidelity, spectral balance, tonal accuracy, sound stage and acoustic fault.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.4 s.121
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• pp.298-309
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• 2007

There are various sounds in the car as much as cars have many mechanical parts. These sounds make various psychological development. The international competition in car markets has continuously required the research about the sound quality of a car. The domestic car makers have also invested a lot of money for the research and development of sound quality. Car axle plays an important role in a vehicle and its NVH development is also important. By this time, NVH development of car axle is mainly based on the reduction of sound pressure level (dBA), which cannot gives, the satisfaction to the customers in view of the sound quality of a vehicle. Therefore, in this paper, a sound quality index evaluating the sound quality of axle noise based on human sensibility is developed.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.6
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• pp.445-451
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• 2003

Booming sound is one of the most important interior sound of a passenger car. The conventional booming noise research was focused on the reduction of the A-weighted sound pressure level. However A-weighted sound pressure level cannot give the whole story about the booming sound of a passenger car. In this paper, we employed sound metrics, which are the subjective parameters, used in psycoacoustics. According to recent research results. the relation between sound metrics and subjective evaluation is very complex and has nonlinear characteristics. In order to estimate this nonlinear relationship, artificial neural network theory has been applied to derivation of sound quality index for booming sound of a passenger car.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11a
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• pp.332.2-332
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• 2002

Booming sound is one of the most important interior sound of a passenger car. The conventional booming noise research was focused on the reduction of the A-weighted sound pressure level. However A-weighted sound pressure level can not give the whole story about the booming sound of a passenger car. In this paper, we employed sound metric which is the subjective parameter used in psychoacoustics. (omitted)

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.654-660
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• 2006

There are various sounds in the car as much as cats have many mechanical parts. These sounds make various sound qualities. The international competition in car markets has continuously required the research about the sound quality of a car. The domestic carmakers have also invested a lot of money for the research and development of sound quality. Car axle plays an important role in a vehicle and its NVH development is also important. By this time, NVH development of car axle is mainly based on the reduction of sound pressure level(dBA), which cannot gives, the satisfaction to the customers in view of the sound quality of a vehicle. Therefore, in this project, a sound quality index evaluating the sound quality of axle noise based on human sensibility is developed and applied to the development of the sound quality of axle noise

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.273-278
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• 2002

Booming sound is one of the most important interior sound of a passenger car. The conventional booming noise research was focused on the reduction of the A-weighted sound pressure level. However A-weighted sound pressure level can not give the whole story about the booming sound of a passenger car. In this paper, we employed sound metric which is the subjective parameter used in psycoacoustics. According to recent research results, the relation between sound metrics and subjective evaluation is very complex and has nonlinear characteristics. In order to estimate this nonlinear relationship, artificial neural network theory has been applied to derivation of sound quality index for booming sound of a passenger car.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.5 s.110
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• pp.457-469
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• 2006

In automotive engineering, the brand sound is one of the important advantage strategies in a car company. For the design of brand sound, the selection of descriptive word for a car sound is one of major works in automotive sound quality research. In this paper, booming and rumbling sound, which are professional words used by sound and vibration engineers are used for the design of brand sound. We employed sound quality metrics, which are used in the psychoacoustics. By most research results, the relationship between subjective evaluations and sound quality metrics has nonlinear characteristics. In order to correlate these subjective evaluations with sound quality metrics, the artificial neural network technology has been applied to two-dimensional sound quality index for a passenger car. These indexes are used for 46 passenger cars, which are samples of the famous cars around the world. Also a preference evaluation for car sound was carried out by sound and vibration engineers. We coupled this preference with booming and rumbling sounds by using artificial neural network. In future, the two dimensional sound and preference index will be very useful to develop brand sound in passenger cars.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.3
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• pp.141-149
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• 2015

In this study, there is an investigation about the sound quality of automotive horn that attached to luxury sedans. In order to define a questionnaire of horn sound quality the factor analysis is conducted. Ten automotive horns are selected for this research and ten passenger cars(nine is luxury sedan and one economy class car). Luxury is used for the questionnaire as an attribute for the sound quality of car horn. The interior noises for ten test cars are recorded and used for the subjective analysis of car horn sound. In the paper, new sound metric for the car horn sound is presented. The new sound metric is used for the objective sound index for the prediction of subjective sound quality of car horn.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11b
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• pp.174-179
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• 2005

In automotive engineering, the brand sound is one of the important advantage strategy in a car company. For the design of brand sound, the selection of descriptive word for a car sound is one of major works in automotive sound quality research. In paper, booming sound and rumbling sound, which are professional words used by NVH engineers are used for the design of brand sound. We employed sound metrics which are the subjective parameter used in psychoacoustics. According to most research results, the relationship between subjective evaluations and sound metrics has nonlinear characteristics and is very complex. In order to link these subjective evaluations to sound metrics, the artificial neural network technology has been applied to two-dimensional sound quality index for a passenger car. These indexes is used for 46 passenger cars, which are samples of famous cars in the world. Also the preference in car sounds is evaluated by the trained NVH engineers. We coupled this preference with booming and rumbling sounds by using artificial neural network. In future, the two -dimensional sound index and preference index are very useful fur the development of brand sound in passenger cars.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.997-1002
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• 2004

Rumbling sound is one of the most important interior sound of a passenger car. The conventional rumbling noise research was focused on the reduction of the A-weighted sound pressure level. However A-weighted sound pressure level can not give the whole story about the rumbling sound of a passenger car. In this paper, we employed sound metric which is the subjective parameter used in psycoacoustics. According to recent research results, the relation between sound metrics and subjective evaluation is very complex and has nonlinear characteristics. In order to estimate this nonlinear relationship, artificial neural network theory has been applied to derivation of sound quality index for rumbling sound of a passenger car.