  Numerical methods can be used to simulate wave propagation in rooms, with
applications in virtual reality and building design. Such methods can be highly
accurate but computationally expensive when simulating high frequencies and
large domains for long simulation times. Moreover, it is common that solutions
are sought for multiple input parameter values, e.g., in design processes in
room acoustics, where different boundary absorption properties are evaluated
iteratively. We present a framework that combines a spectral element method
(SEM) and a reduced basis method (RBM) to achieve a computational cost
reduction for parameterized room acoustic simulations. The SEM provides low
dispersion and dissipation properties due to the high-order discretization and
the RBM reduces the computational burden further when parametrizing the
boundary properties for both frequency-independent and dependent conditions.
The problem is solved in the Laplace domain, which avoids instability issues on
the reduced model. We demonstrate that the use of high-order discretization and
model order reduction has significant advantages for room acoustics in terms of
computational efficiency and accuracy.
