Generalization of dimension-based statistical learning in word recognition

Recent research demonstrates that the diagnosticity of an acoustic dimension for speech categorization is relative to its relationship to the evolving distribution of dimensional regularity across time, and not simply to its fixed value along the dimension. Two studies examine the nature of this dimension-based statistical learning in online word recognition, testing generalization of learning across talkers and across phonetic categories. The results indicate that dimension-based statistical learning generalizes across talkers, but is specific to experienced phonetic categories.