LAUSR

When objects collide they vibrate and emit sound. Physical laws govern these collisions and subsequent vibrations. As a result, sound contains information about objects (density/hardness/size/shape), and the manner in which they collide (bouncing/rolling/scraping). Everyday experience suggests that human listeners have some ability to discern material and kinematics from impact sounds. However, the accuracy of these perceptual inferences remains unclear, and the underlying mechanisms are uncharacterized. Listeners could rely on stored templates for particular familiar objects. Alternatively, we could infer generative parameters for a sound via probabilistic inference in an internal model of the generative process. To explore these possibilities we constructed a generative model of impact sounds, modeling sounds as the convolution of a time-varying impact force with the impulse responses (IRs) of two objects. The force was modeled as a function of mass, hardness and impact velocity. IRs were measured from ...