Speech segmentation by statistical learning depends on attention

TitleSpeech segmentation by statistical learning depends on attention
Publication TypeJournal Article
Year of Publication2005
AuthorsToro JM, Sinnett S, Soto-Faraco S
JournalCognition
Volume97
Issue2
PaginationB25–34
Date Published09/2005
ISSN0010-0277
KeywordsAttention, Cues, Humans, Language, Recognition (Psychology), Speech, Verbal Learning
Abstract

We addressed the hypothesis that word segmentation based on statistical regularities occurs without the need of attention. Participants were presented with a stream of artificial speech in which the only cue to extract the words was the presence of statistical regularities between syllables. Half of the participants were asked to passively listen to the speech stream, while the other half were asked to perform a concurrent task. In Experiment 1, the concurrent task was performed on a separate auditory stream (noises), in Experiment 2 it was performed on a visual stream (pictures), and in Experiment 3 it was performed on pitch changes in the speech stream itself. Invariably, passive listening to the speech stream led to successful word extraction (as measured by a recognition test presented after the exposure phase), whereas diverted attention led to a dramatic impairment in word segmentation performance. These findings demonstrate that when attentional resources are depleted, word segmentation based on statistical regularities is seriously compromised.

URLhttp://dx.doi.org/10.1016/j.cognition.2005.01.006
DOI10.1016/j.cognition.2005.01.006