One measure of perceived quality in a new car is how easily the passengers can communicate. This includes communication between the passengers and also communication to the vehicle itself, as features such as Bluetooth and voice activated controls become increasingly common. Articulation Index (AI) has long been the standard in the automotive industry for evaluating the ease of communication. Previous studies have explained that AI, however, only evaluates the background noise that surrounds the listener; and does not capture changes in modulation of sound before reaching the listener. The telecommunication and construction industries have used Speech Transmission Index (STI) as a measure of communication. This method incorporates the masking effect of background noise, and modulation of the speech signal along the transmission path. This study focused to understand STI, cascade to component characteristics and modify characteristics to improve speech transmission inside vehicles. As first step, the appropriateness of the STI index was confirmed. The study then focused to establish which components in the vehicle interior influence the sound path. The contribution and path of sound ray was calculated using the Ray tracing simulation method and the simulation results were confirmed using windowing study in a vehicle. Based on the contribution study, high contribution component's acoustic characteristics were modified to improve STI. Through the use of these steps, a vehicle design proposal was developed that reduced the background noise at the listener and improved the speech transmission inside the vehicle. This study resulted in a prediction method which can be used to develop STI for passenger cars.
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