4 accepted papers
Diffracted scattering and occlusion are important acoustic effects in interactive auralization and noise control applications, typically requiring expensive numerical simulation. We propose training a convolutional neural network to map from a convex scatterer's cross-section to a 2D slice of the re…
We study the detailed temporal evolution of echo density in impulse responses for applications in acoustic analysis and rendering on general environments. For this purpose, we propose a smooth sorted density measure that yields an intuitive trend of echo density growth with time. This is fitted with…
Recent work on acoustic parameter estimation indicates that geometric room volume can be useful for modeling the character of an acoustic environment. However, estimating volume from audio signals remains a challenging problem. Here we propose using a convolutional neural network model to estimate t…
A powerful and flexible approach to record or encode a spatial sound scene is through spherical harmonics (SHs), or Ambisonics. An SH-encoded scene can be rendered binaurally by applying SH-encoded head-related transfer functions (HRTFs). Limitations of the recording equipment or computational const…