When statistics collide: The use of transitional and phonotactic probability cues to word boundaries

Mem Cognit. 2021 Oct;49(7):1300-1310. doi: 10.3758/s13421-021-01163-4. Epub 2021 Mar 9.

Abstract

Statistical regularities in linguistic input, such as transitional probability and phonotactic probability, have been shown to promote speech segmentation. It remains unclear, however, whether or how the combination of transitional probabilities and subtle phonotactic probabilities influence segmentation. The present study provides a fine-grained investigation of the effects of such combined statistics. Adults (N = 81) were tested in one of two conditions. In the Anchor condition, they heard a continuous stream of words with small differences in phonotactic probabilities. In the Uniform condition, all words had comparable phonotactic probabilities. In both conditions, transitional probability was stronger in words than in part-words. Only participants from the Anchor condition preferred words at test, indicating that the combination of transitional probabilities and subtle phonotactic probabilities may facilitate speech segmentation. We discuss the methodological implications of our findings, which demonstrate that even small phonotactic variations should be accounted for when investigating statistical speech segmentation.

Keywords: Language development; Phonotactics; Speech segmentation; Statistical learning.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Cues*
  • Humans
  • Phonetics
  • Probability
  • Speech
  • Speech Perception*