This paper describes three psychoacoustic experiments that evaluated the perceptual quality of sounds generated from a new wavelet-based synthesis technique. The synthesis technique provides a method for modeling and synthesizing perceptually compelling sound. The experiments define a methodology for evaluating the effectiveness of any synthesized sound. An identification task and a context-based rating task evaluated the perceptual quality of individual sounds. These experiments confirmed that the wavelet technique synthesizes a wide variety of compelling sounds from a small model set. The third experiment obtained sound similarity ratings. Psychological scaling methods were applied to the similarity ratings to generate both spatial and network models of the perceptual relations among the synthesized sounds. These analysis techniques helped to refine and extend the sound models. Overall, the studies provided a framework to validate synthesized sounds for a variety of applications including virtual reality and data sonification systems.

This paper describes a new technique for synthesizing realistic sounds for virtual environments. The four-phase technique described uses wavelet analysis to create a sound model. Parameters are extracted from the model to provide dynamic sound synthesis control from a virtual environment simulation. Sounds can be synthesized in real time using the fast inverse wavelet transform. Perceptual experiment validation is an integral part of the model development process. This paper describes the four-phase process for creating the parameterized sound models. Several developed models and perceptual experiments for validating the sound synthesis veracity are described. The developed models and results demonstrate proof of the concept and illustrate the potential of this approach.