  We extend our previous work [F. Henr\'iquez and J. S. Hesthaven,
arXiv:2403.02847 (2024)] to the linear, second-order wave equation in bounded
domains. This technique, referred to as the Laplace Transform Reduced Basis
(LT-RB) method, uses two widely known mathematical tools to construct a fast
and efficient method for the solution of linear, time-dependent problems: The
Laplace transform and the Reduced Basis method, hence the name.
  The application of the Laplace transform yields a time-independent problem
parametrically depending on the Laplace variable. Following the two-phase
paradigm of the RB method, firstly in an offline stage we sample the Laplace
parameter, compute the full-order or high-fidelity solution, and then resort to
a Proper Orthogonal Decomposition (POD) to extract a basis of reduced
dimension. Then, in an online phase, we project the time-dependent problem onto
this basis and proceed to solve the evolution problem using any suitable
time-stepping method. We prove exponential convergence of the reduced solution
computed by the LT-RB method toward the high-fidelity one as the dimension of
the reduced space increases.
  Finally, we present a set of numerical experiments portraying the performance
of the method in terms of accuracy and, in particular, speed-up when compared
to the full-order model.
