Fast auralization using radial basis functions type of artificial neural network techniques

Abstract This work presents a new technique to produce fast and reliable auralizations with a computer code for room acoustics simulation. It discusses the binaural room impulse responses generation classic method and presents a new technique using radial basis functions type of artificial neural networks. The radial basis functions type of artificial neural networks is briefly presented and its training and testing procedures are discussed. The artificial neural network models the filtered head-related impulse responses for 64,442 directions uniformly distributed around the head with a significant reduction in computational cost of around 90% in the generation of binaural impulse responses. It is shown that the filtered head-related impulse responses calculated with the classical convolution method and with the artificial neural network technique are almost indistinguishable. It is concluded that the new technique produces fastest and reliable binaural room impulse responses for auralization purposes.

[1]  Bernie Mulgrew,et al.  Applying radial basis functions , 1996, IEEE Signal Process. Mag..

[2]  Heinrich Kuttruff,et al.  Room acoustics , 1973 .

[3]  J. Borish.  Extension of the image model to arbitrary polyhedra , 1984 .

[4]  John Moody,et al.  Fast Learning in Networks of Locally-Tuned Processing Units , 1989, Neural Computation.

[5]  Simon Haykin,et al.  Neural Networks and Learning Machines , 2010 .

[6]  Ning Xiang,et al.  Introduction to the Special Issue on Room Acoustic Modeling and Auralization. , 2019, The Journal of the Acoustical Society of America.

[7]  Roberto A. Tenenbaum,et al.  Auralization generated by modeling HRIRs with artificial neural networks and its validation using articulation tests , 2018 .

[8]  M. Vorländer.  Simulation of the transient and steady‐state sound propagation in rooms using a new combined ray‐tracing/image‐source algorithm , 1989 .

[9]  Henrik Møller.  Fundamentals of binaural technology , 1991 .

[10]  Durand R. Begault,et al.  3-D Sound for Virtual Reality and Multimedia Cambridge , 1994 .

[11]  Felipe Otondo,et al.  A new method for the radiation representation of musical instruments in auralizations. , 2005 .

[12]  Christopher M. Bishop,et al.  Neural networks for pattern recognition , 1995 .

[13]  John G. Proakis,et al.  Digital Signal Processing: Principles, Algorithms, and Applications , 1992 .

[14]  R. Wilcox.  Introduction to Robust Estimation and Hypothesis Testing , 1997 .

[15]  Lauri Savioja,et al.  Overview of geometrical room acoustic modeling techniques. , 2015, The Journal of the Acoustical Society of America.

[16]  Steffen Lepa,et al.  A spatial audio quality inventory for virtual acoustic environments (SAQI) , 2014 .

[17]  Trevor J. Cox,et al.  Diffusor application in rooms , 2000 .

[18]  Jens Blauert,et al.  Principles of binaural room simulation , 1992 .

[19]  Mendel Kleiner,et al.  Auralization-An Overview , 1993 .

[20]  Subhash C. Kak,et al.  The Number Theoretic Hilbert Transform , 2013, Circuits, Systems, and Signal Processing.

[21]  Jacques Martin,et al.  Binaural room acoustics simulation: Practical uses and applications , 1992 .

[22]  Samuel D. Conte,et al.  Elementary Numerical Analysis: An Algorithmic Approach , 1975 .

[23]  Murray Hodgson,et al.  Comparison of Predicted, Measured and Auralized Sound Fields with Respect to Speech Intelligibility in Classrooms Using CATT-Acoustic and ODEON , 2008 .

[24]  Jason E Summers,et al.  What exactly is meant by the term "auralization?". , 2008, The Journal of the Acoustical Society of America.

[25]  Jens Blauert,et al.  Binaural room simulation , 1991 .

[26]  Michael Vorländer,et al.  A round robin on room acoustical simulation and auralization. , 2019, The Journal of the Acoustical Society of America.

[27]  Jianxin Peng.  Feasibility of subjective speech intelligibility assessment based on auralization , 2005 .

[28]  Tapio Lokki,et al.  Physically-based auralization : design, implementation, and evaluation , 2002 .

[29]  A. M. Ondet,et al.  Modeling of sound propagation in fitted workshops using ray tracing , 1989 .

[30]  Roberto A. Tenenbaum,et al.  Hybrid method for numerical simulation of room acoustics with auralization: part 1 - theoretical and numerical aspects , 2007 .

[31]  D. Broomhead,et al.  Radial Basis Functions, Multi-Variable Functional Interpolation and Adaptive Networks , 1988 .

[32]  Jin Yong Jeon,et al.  A tutorial on scattering and diffusion coefficients for room acoustic surfaces , 2006 .