  In the present paper we use a range of modeling techniques to investigate
whether an abstract phone could emerge from exposure to speech sounds. In
effect, the study represents an attempt for operationalize a theoretical device
of Usage-based Linguistics of emergence of an abstraction from language use.
Our quest focuses on the simplest of such hypothesized abstractions. We test
two opposing principles regarding the development of language knowledge in
linguistically untrained language users: Memory-Based Learning (MBL) and
Error-Correction Learning (ECL). A process of generalization underlies the
abstractions linguists operate with, and we probed whether MBL and ECL could
give rise to a type of language knowledge that resembles linguistic
abstractions. Each model was presented with a significant amount of
pre-processed speech produced by one speaker. We assessed the consistency or
stability of what these simple models have learned and their ability to give
rise to abstract categories. Both types of models fare differently with regard
to these tests. We show that ECL models can learn abstractions and that at
least part of the phone inventory and grouping into traditional types can be
reliably identified from the input.
