Statistical learning across passive listening adjusts perceptual weights of speech input dimensions.

Statistical learning across passive exposure has been theoretically situated with unsupervised learning. However, when input statistics accumulate over established representations - like speech syllables, for example - there is the possibility that prediction derived from activation of rich, existing representations may support error-driven learning. Here, across five experiments, we present evidence for error-driven learning across passive speech listening. Young adults passively listened to a string of eight beer - pier speech tokens with distributional regularities following either a canonical American-English acoustic dimension correlation or a correlation reversed to create an accent. A sequence-final test stimulus assayed the perceptual weight - the effectiveness - of the secondary dimension in signaling category membership as a function of preceding sequence regularities. Perceptual weight flexibly adjusted according to the passively experienced regularities even when the preceding regularities shifted on a trial-by-trial basis. The findings align with a theoretical view that activation of established internal representations can support learning across statistical regularities via error-driven learning. At the broadest level, this suggests that not all statistical learning need be unsupervised. Moreover, these findings help to account for how cognitive systems may accommodate competing demands for flexibility and stability: instead of overwriting existing representations when short-term input distributions depart from the norms, the mapping from input to category representations may be dynamically - and rapidly - adjusted via error-driven learning from predictions derived from internal representations.

The Principle of Least Effort and Comprehension of Spoken Sentences by Younger and Older Adults.

There is considerable evidence that listeners' understanding of a spoken sentence need not always follow from a full analysis of the words and syntax of the utterance. Rather, listeners may instead conduct a superficial analysis, sampling some words and using presumed plausibility to arrive at an understanding of the sentence meaning. Because this latter strategy occurs more often for sentences with complex syntax that place a heavier processing burden on the listener than sentences with simpler syntax, shallow processing may represent a resource conserving strategy reflected in reduced processing effort. This factor may be even more important for older adults who as a group are known to have more limited working memory resources. In the present experiment, 40 older adults (M age = 75.5 years) and 20 younger adults (M age = 20.7) were tested for comprehension of plausible and implausible sentences with a simpler subject-relative embedded clause structure or a more complex object-relative embedded clause structure. Dilation of the pupil of the eye was recorded as an index of processing effort. Results confirmed greater comprehension accuracy for plausible than implausible sentences, and for sentences with simpler than more complex syntax, with both effects amplified for the older adults. Analysis of peak pupil dilations for implausible sentences revealed a complex three-way interaction between age, syntactic complexity, and plausibility. Results are discussed in terms of models of sentence comprehension, and pupillometry as an index of intentional task engagement.