Artikel,
Bayesian Inference Approach to Room-Acoustic Modal Analysis
AIP Conference Proceedings, 1553 (1): 38--45 (August 2013)
DOI: 10.1063/1.4819981
Zusammenfassung
Spectrum estimation is a problem common to many fields of physics,
science, and engi- neering, and it has thus received a great deal
of attention from the Bayesian data analysis commu- nity. In room
acoustics, the modal or frequency response of a room is important
for diagnosing and remedying acoustical defects. The physics of a
sound field in a room dictates a model comprised of exponentially
decaying sinusoids. Continuing in the tradition of the seminal work
of Bretthorst and Jaynes, this work contributes an approach to analyzing
the modal responses of rooms with a time-domain model. Room acoustic
spectra are constructed of damped sinusoids, and the model- based
approach allows estimation of the number of sinusoids in the signal
as well as their frequen- cies, amplitudes, damping constants, and
phase delays. The frequency-amplitude spectrum may be most useful
for characterizing a room, but in some settings the damping constants
are of primary interest. This is the case for measuring the absorptive
properties of materials, for example. A fur- ther challenge of the
room acoustic spectrum problem is that modal density increases quadratically
with frequency. At a point called the Schroeder frequency, adjacent
modes overlap enough that the spectrum particularly when estimated
with the discrete Fourier transform can be treated as a continuum.
The time-domain, model-based approach can resolve overlapping modes
and in some cases be used to estimate the Schroeder frequency. The
proposed approach addresses the issue of filtering and preprocessing
in order for the sampling to accurately identify all present room
modes with their quadratically increasing density.
