Abstract
Sounds generated by new vehicles are important for characterization of brand
of car manufacture. Consequently automotive manufacturers are interested in how to turn
customer preferences of sounds into achievable engineering targets; sound quality engineering.
In this paper the sound index is developed based on artificial neural networks (ANNs) to
predict the sound quality of a new passenger vehicle without any jury evaluation. This index
gives information for the customer preferences regards the sound quality of a new car. Such
evaluations are costly and time consuming. The sound index is developed based on two major
sounds such as booming and rumbling. These two sounds are dominant components in the
compartment of a passenger car.
Keywords - Brand Sound, Sound Quality, Automotive, Sound Index, Passenger Car