Objective evaluation of interior sound quality in passenger cars during acceleration

Abstract

While driving a passenger car, a driver can hear many sorts of sounds inside the car. Among them, the booming and rumbling sounds are classified as the dominant sound characteristics of passenger cars. A sound quality index evaluating the quality of these two sounds objectively is therefore required and is developed by using an artificial neural network (ANN) in the present paper. Throughout this research, the booming sound and rumbling sound were found to be effectively related to the loudness, sharpness and roughness, while the fluctuation strength is not related to these sounds. These subjective parameters are sound metrics in psychoacoustics and are used as the input of ANN. For the training process of the ANN, 150 interior sounds with booming sound quality and 150 interior sounds with rumbling sound quality of various subjective rates have been synthesized, referring to the sound characteristics of passenger cars. The other 16 interior sounds of passenger cars were obtained by measurement. The booming sound qualities and rumbling sound qualities for these interior sounds were subjectively evaluated by 21 persons for the target of the ANN. After the ANN was trained, the two outputs of this ANN were used for the booming index and rumbling index, respectively. These outputs were tested in the evaluation of the sound quality of the interior sounds which were measured inside of the 16 passenger cars. The preference rate for the 30 passenger cars was evaluated by using these two developed sound indexes. These indexes were also successfully applied to the enhancement of the interior sound quality for a developmental passenger car.