Exploring Sound Change Over Time: A Review of Computational and Human Perception
This is an incremental review that synthesizes existing methods to address a gap in the intersection of computational and human perception for linguists and researchers in computational linguistics.
The paper reviews computational and human perception approaches for studying sound change over time, highlighting their complementary roles in achieving a more comprehensive understanding, and calls for comparative studies on datasets to investigate historical influences on ongoing changes.
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.