Abstrakt
Theories of phonology claim variously that phonological elements are either innate or emergent, and either substance-full or substance-free. A hitherto underdeveloped source of evidence for choosing between the four possible combinations of these claims lies in showing precisely how a child can acquire phonological elements.
This article presents computer simulations that showcase a learning algorithm with which the learner creates phonological elements from a large number of sound-meaning pairs. In the course of language acquisition, phonological features gradually emerge both bottom-up and top-down, that is, both from the phonetic input (i.e., sound) and from the semantic or morphological input (i.e., structured meaning).
In our computer simulations, the child's phonological features end up with emerged links to sounds (phonetic substance) as well as with emerged links to meanings (semantic substance), without containing either phonetic or semantic substance. These simulations therefore show that emergent substance-free phonological features are learnable.
In the absence of learning algorithms for linking innate features to the language-specific variable phonetic reality, as well as the absence of learning algorithms for substance-full emergence, these results provide a new type of support for theories of phonology in which features are emergent and substance-free.