4.4 Article

The surprising power of statistical learning: When fragment knowledge leads to false memories of unheard words

Journal

JOURNAL OF MEMORY AND LANGUAGE
Volume 60, Issue 3, Pages 351-367

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jml.2008.10.003

Keywords

Statistical learning; Transition probabilities; Word segmentation; Cue integration; Perceptual cues to word learning

Funding

  1. McDonnell Foundation [21002089]
  2. European Commission

Ask authors/readers for more resources

Word-segmentation, that is, the extraction of words from fluent speech, is one of the first problems language learners have to master. It is generally believed that statistical processes, in particular those tracking transitional probabilities (TPs), are important to word-segmentation. However, there is evidence that word forms are stored in memory formats differing from those that can be constructed from TPs, i.e. in terms of the positions of phonemes and syllables within words. In line with this view, we show that TP-based processes leave learners no more familiar with items heard 600 times than with phantom-words not heard at all if the phantom-words have the same statistical structure as the occurring items. Moreover, participants are more familiar with phantom-words than with frequent syllable combinations. In contrast, minimal prosody-like perceptual cues allow learners to recognize actual items. TPs may well signal co-occurring syllables; this, however, does not seem to lead to the extraction of word-like units. We review other, in particular prosodic, cues to word-boundaries which may allow the construction of positional memories while not requiring language-specific knowledge, and suggest that their contributions to word-segmentation need to be reassessed. (C) 2008 Elsevier Inc. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.4
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available