  The exploration of the universe is experiencing a huge development thanks to
the success and possibilities of today's major space telescope missions which
can generate measurements and images with a resolution 100 times higher than
their precedents. This big ecosystem of observations, aimed at expanding the
limits of known science, can be analyzed using personal computers thanks to the
implementation of interoperable Virtual Observatory (VO) technologies and
massive portals of stellar catalogs and databases. In this context of global
analysis of astronomical big data, sonification has the potential of adding a
complementary dimension to visualization, enhancing the accessibility of the
archives, and offering an alternative strategy to be used when overlapping
issues and masking effects are found in purely graphical representations. This
article presents a collection of sonification and musification prototypes that
explore the case studies of the MILES and STELIB stellar libraries from the
Spanish Virtual Observatory (SVO), and the Kepler Objects of Interest light
curve database from the Space Telescope Science Institute archive (STScI). The
work makes use of automation, machine learning, and deep learning algorithms to
offer a palette of resources that could be used in future developments oriented
towards an auditory virtual observatory proposal. It includes a user study that
provides qualitative and quantitative feedback from specialized and
non-specialized users in the fields of Music and Astronomy.
