Abstract
Investigating audition with a generative model of impact sounds
The Journal of the Acoustical Society of America, Vol.141(5 Supplement), pp.3901-3901
05/2017
DOI: 10.1121/1.4988777
Abstract
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 a range of objects using contact speakers and microphones to measure an object’s effect on vibrational input. IRs for arbitrary objects were generated via interpolation between recorded examples. The model generates compelling renditions of impact sounds. Physically motivated alterations to the force and/or IRs produced physically plausible synthetic impact sounds that can be used in perceptual experiments.
Details
- Title: Subtitle
- Investigating audition with a generative model of impact sounds
- Creators
- James Traer - Brain and Cognit. Sci., MIT, 77 Massachusetts Ave, Cambridge, MA 02139, jtraer@mit.eduJosh McDermott - Brain and Cognit. Sci., MIT, 77 Massachusetts Ave, Cambridge, MA 02139, jtraer@mit.edu
- Resource Type
- Abstract
- Publication Details
- The Journal of the Acoustical Society of America, Vol.141(5 Supplement), pp.3901-3901
- DOI
- 10.1121/1.4988777
- NLM abbreviation
- J Acoust Soc Am
- ISSN
- 0001-4966
- eISSN
- 1520-8524
- Publisher
- Acoustical Society of America
- Number of pages
- 1
- Date published
- 05/2017
- Academic Unit
- Psychological and Brain Sciences; Iowa Neuroscience Institute
- Record Identifier
- 9984065466802771
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