Physically informed car engine sound synthesis for virtual and augmented environments

The richness of crossmodal feedback in car driving makes it an engaging, complex, yet “natural” activity. Audition plays an important role, as the engine sound, perceived in the cabin, conveys relevant cues about the vehicle motion. In this paper, we introduce a procedural and physically informed model for synthetic combustion engine sound, as an effective, flexible and computationally efficient alternative to sample-based and analysis/resynthesis approaches. The sound model, currently being developed as Max/MSP external, has been integrated in GeneCars, a driving simulator environment for industrial sound design, and SkAT Studio, a demonstration framework for the rapid creation of audio processing workflows.