# Micah Shepherd, Xi Chen, Timothy W. Leishman, Scott D.Sommerfeldt Acoustics Research Group

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Experimental Equalization of a One-Dimensional Sound Field Using Energy Density and a Parametric Equalizer Micah Shepherd, Xi Chen, Timothy W. Leishman, Scott D.Sommerfeldt…TRANSCRIPT

Experimental Equalization of a One-Dimensional Sound Field Using Energy Density and a Parametric Equalizer
Micah Shepherd, Xi Chen, Timothy W. Leishman,
Scott D.Sommerfeldt
Acoustics Research Group
Department of Physics and Astronomy
Brigham Young University
148th Meeting of the Acoustical Society of America
18 November 2004
Background and Traditional Technique
Background
Sound fields in rooms do not have ideal responses
Sound field equalization compensates for room effects using filters
Traditional techniques
Excite room using pink noise
Measure pressure response at one location
Cut and boost in nth octave bands using graphic equalizer to produce desired response
Better control using parametric equalizers
Variable frequency
Variable Q
Problems
Spatial variance of sound field
Microphone at nodes
Limited frequency and gain adjustment
Need for a better approach
Search for an Improved Technique
Measure transfer function between source and receiver in 1-D sound field
Three cases
Single point mean-squared pressure
Spatially averaged mean-squared pressure (potential energy density)
Single point total energy density
Use normalized inverses of the responses as equalization filters
Experimental Setup
Energy Density
Pressure gradient method
Estimate particle velocity using pressure gradient
Energy Density is then
2 microphone transfer function method
Developed by Chung and Blaser
Solve for incident and reflected pressure and reflection coefficients at microphone positions
Derive particle velocity and energy density from result
Difference in ED Estimations
Unequalized Field
Mean-Squared Pressure Field
Energy Density Field
Ideal Inverse Filters From Measured Field
Ideal Equalized Pressure Fields
Mean-Squared Pressure EQ
Energy Density EQ
Comparison of Ideal Energy Density
Filter and Parametric EQ Filter
Equalized Pressure Fields
Parametric ED EQ
Ideal ED EQ
Spatially Averaged Pressure Responses: Ideal and Parametric
Conclusions
Energy density equalization approximates spatially averaged pressure equalization in a 1-D sound field
A discrete ED measurement can be used to equalize a 1-D sound field better than a discrete pressure measurement
Parametric equalizers can be used to approximate ideal ED filters, but with notable errors
Future work
Conduct more general tests in a 1-D field with variable side-branch source positions
Test energy density equalization methods in 3-D sound fields
Test energy density equalization methods using multiple sources
Develop adaptive filtering techniques
Thank you

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