While I'm primarily interested in molecular normal modes, the question could also apply to calculating phonon spectra / vibrations in solids.
There are many machine learning approaches to calculate energies of molecules and solids. Some have even been used for molecular dynamics and geometry optimizations.
In principal, one could use the ML potential energy surface to derive the mass-weighted Hessian matrix, and solve for eigenvalues and eigenvectors. (For example, one could test whether the resulting vibrational frequencies are accurate.)
Are there existing packages (e.g., in Python) which calculate the mass-weighted Hessian from a ML potential, convert units to frequencies, and compare the normal modes?