Rough Set Based Modeling and Visualization of the Acoustic Field Around the Human Head

The presented research aims at modeling acoustical wave propagation phenomena by applying rough set theory in a novel manner. In a typical listening environment sound intensity is determined by numerous factors: a distance from a sound source, signal levels and frequencies, obstacles’ locations and sizes. Contrarily, a free-field is characterized by direct, unimpeded propagation of the acoustical waves. The proposed approach is focused on processing sound field measurements performed in an anechoic chamber, collected by a dedicated acoustic probe, comprising thousands of datapoints for six signal frequencies, with and without the presence of a dummy head in a free-field. The rough set theory is applied for modeling the influence of an obstacle that a dummy head creates in a free-field and the effects of the head acoustic interferences, shading and diffraction. A data pre-processing method is proposed, involving coordinate system transformation, data discretization, and classification. Four rule sets are acquired, and achieved accuracy and coverage are assessed. Final results allow simplification of the model and new method for visualization.

[1]  Giulio Cengarle,et al.  Comparison of Anemometric Probe and Tetrahedral Microphones for Sound Intensity Measurements , 2011 .

[2]  Finn Jacobsen,et al.  Measurement of sound intensity: p-u probes versus p-p probes , 2005 .

[3]  Bozena Kostek,et al.  Measurements and Visualization of Sound Intensity around the Human Head Using Acoustic Vector Sensor , 2014 .

[4]  Bozena Kostek,et al.  Measurements and Visualization of Sound Intensity Around the Human Head in Free Field Using Acoustic Vector Sensor , 2015 .

[5]  Jozef Kotus,et al.  Application of passive acoustic radar to automatic localization, tracking and classification of sound sources , 2010, 2010 2nd International Conference on Information Technology, (2010 ICIT).

[6]  Finn Jacobsen,et al.  A comparison of two different sound intensity measurement principles , 2005 .

[7]  Marcin S. Szczuka,et al.  A New Version of Rough Set Exploration System , 2002, Rough Sets and Current Trends in Computing.

[8]  Jozef Kotus Multiple sound sources localization in free field using acoustic vector sensor , 2013, Multimedia Tools and Applications.

[9]  de Bree The Microflown, an acoustic particle velocity sensor , 2003 .

[10]  S. Weyna,et al.  Identification of reflection, diffraction and scattering effects in realacoustic flow fields , 2003 .

[11]  Finn Jacobsen,et al.  Sound intensity and its measurement and applications , 2003 .

[12]  Jerzy W. Grzymala-Busse,et al.  Rough Sets , 1995, Commun. ACM.

[13]  R. Raangs,et al.  A Low-Cost Intensity Probe , 2003 .

[14]  Masakazu Iwaki,et al.  Anechoic Measurements of Particle-Velocity Probes Compared to Pressure Gradient and Pressure Microphones , 2006 .

[15]  Juha Merimaa,et al.  Measurement, Analysis, and Visualization of Directional Room Responses , 2001 .