Insightful Knowledge of Double Onset Constituency via the Standard and a Modified Optimality Theory

The current study reveals that the constraint-based standard optimality theory can better predict the co-occurrence of double onsets, whereas a corpus-data based optimality theory, which replaces a constraint tableau with a corpus-data table, can concentrate on the limited well-formed candidates, accounting more straightforwardly for interactions of the adjacent segments. In phonological processes, linear generative phonology is more clean-cut to explain the phonetic feature that influences adjacent segments. Optimality theory can have a pragmatic mode developed for the general public. As such, a new framework can make easier predictions and gain more insightful knowledge of double onset constituency, and does not have to resort to much terminology and sheer candidates generated, based on constraints for optimal outputs.