  Computational and human perception are often considered separate approaches
for studying sound changes over time; few works have touched on the
intersection of both. To fill this research gap, we provide a pioneering review
contrasting computational with human perception from the perspectives of
methods and tasks. Overall, computational approaches rely on computer-driven
models to perceive historical sound changes on etymological datasets, while
human approaches use listener-driven models to perceive ongoing sound changes
on recording corpora. Despite their differences, both approaches complement
each other on phonetic and acoustic levels, showing the potential to achieve a
more comprehensive perception of sound change. Moreover, we call for a
comparative study on the datasets used by both approaches to investigate the
influence of historical sound changes on ongoing changes. Lastly, we discuss
the applications of sound change in computational linguistics, and point out
that perceiving sound change alone is insufficient, as many processes of
language change are complex, with entangled changes at syntactic, semantic, and
phonetic levels.
