Why Adult Language Learning is Harder: A Computational Model of the Consequences of Cultural Selection for Learnability.

This paper reports on a limited model of language evolution that incorporates transmission noise and errorful learning as sources of variation. The model illustrates how the adaptation of language to the statistical learning mechanisms of infants may be a factor in the apparent ceiling on adult second language achievement. The model is limited in its focus to only phonotactics because the probabilistic imbalances that have been found in phonotactics have been found to be effective cues in the very first language learning task, speech segmentation (Saffran & Theissen, 2003; Mattys & Jusczyk, 2001), and in the organization of lexical memory (Vitevitch, Luce, Pisoni & Auer, 1999). The argument that this model supports is that these probabilistic imbalances are the result of the cultural selection of more learnable variants across generations of learners, and that this process has produced sequences that help the child learner while confounding the adult learner. The child learner is aided by specific phonotactic cues that correlate with word and syllable boundaries (e.g. the English prohibition on word initial ‘-ng’ and Czech word-final voicelessness). These cues are often invisible or misleading to the adult learner (e.g. Broselow