A Sparsity Measure for Echo Density Growth in General Environments

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 a general power-law model motivated from theoretical considerations. We validate the framework against theory on simple room geometries and present experiments on measured and numerically simulated impulse responses in complex scenes. Our results show that the growth power of echo density is a promising statistical parameter that shows noticeable, consistent differences between indoor and outdoor responses, meriting further study.

[1]  H. Gaskell The precedence effect , 1983, Hearing Research.

[2]  Anders Gade,et al.  Acoustics in Halls for Speech and Music , 2014 .

[3]  Jonathan S. Abel,et al.  A Simple, Robust Measure of Reverberation Echo Density , 2006 .

[4]  Tomohiro Nakatani,et al.  The reverb challenge: A common evaluation framework for dereverberation and recognition of reverberant speech , 2013, 2013 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics.

[5]  Vesa Välimäki,et al.  Fifty Years of Artificial Reverberation , 2012, IEEE Transactions on Audio, Speech, and Language Processing.

[6]  Jonathan S. Abel,et al.  A Digital Reverberator Modeled After the Scattering of Acoustic Waves by Trees in a Forest , 2008 .

[7]  Damian Murphy,et al.  OpenAIR: An Interactive Auralization Web Resource and Database , 2010 .

[8]  J. Polack Playing billiards in the concert hall: The mathematical foundations of geometrical room acoustics , 1993 .

[9]  Ming C. Lin,et al.  Efficient and Accurate Sound Propagation Using Adaptive Rectangular Decomposition , 2009, IEEE Transactions on Visualization and Computer Graphics.

[10]  D. Manocha,et al.  Acoustic pulse propagation in an urban environment using a three-dimensional numerical simulation. , 2014, The Journal of the Acoustical Society of America.

[11]  Nikunj Raghuvanshi,et al.  Parametric directional coding for precomputed sound propagation , 2018, ACM Trans. Graph..

[12]  Emanuel A. P. Habets,et al.  Feedback Delay Networks: Echo Density and Mixing Time , 2017, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[13]  Jean-Dominique Polack,et al.  Using Matching Pursuit for Estimating Mixing Time Within Room Impulse Responses , 2009 .

[14]  S. Weinzierl,et al.  Perceptual Evaluation of Physical Predictors of the Mixing Time in Binaural Room Impulse Responses , 2010 .

[15]  Vesa Välimäki,et al.  Modeling Sparsely Reflecting Outdoor Acoustic Scenes Using the Waveguide Web , 2017, IEEE/ACM Transactions on Audio, Speech, and Language Processing.