  The Helmholtz equation has been used for modelling the sound pressure field
under a harmonic load. Computing harmonic sound pressure fields by means of
solving Helmholtz equation can quickly become unfeasible if one wants to study
many different geometries for ranges of frequencies. We propose a machine
learning approach, namely a feedforward dense neural network, for computing the
average sound pressure over a frequency range. The data is generated with
finite elements, by numerically computing the response of the average sound
pressure, by an eigenmode decomposition of the pressure. We analyze the
accuracy of the approximation and determine how much training data is needed in
order to reach a certain accuracy in the predictions of the average pressure
response.
