How Transitional Probabilities and the Edge Effect Contribute to Listeners’ Phonological Bootstrapping Success

ABSTRACT

Much of what we know about the development of listeners’ word segmentation strategies originates from the artificial language-learning literature. However, many artificial speech streams designed to study word segmentation lack a salient cue found in all natural languages: utterance boundaries. In this study, participants listened to a speech-stream containing one of three sets of word boundary cues: transitional probabilities between syllables (TP Condition), silences marking utterance boundaries (UB Condition), or a combination of both cues (TP + UB Condition). Recognition of the trained words and rule words (words not in language, but conforming to its phonotactic structure) was tested. Participants performed equally well in the TP + UB and UB Conditions, scoring above chance on both trained and rule words. Performance in the TP condition, however, was at chance. Our results suggest that attention to UBs is a particularly effective strategy for finding words in speech, possibly providing a language-general solution to the word segmentation problem.

Acknowledgments

We thank Tania Zamuner for her theoretical input and comments on an earlier draft of this manuscript and Jaspal Brar for assistance in testing participants. Preliminary results were presented at the International Conference on Infant Studies 2012 in Minneapolis, Minnesota.

Funding

This work was supported by a Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery grant awarded to EKJ, a SSHRC grant awarded to EKJ, and an NSERC USRA (Undergraduate Student Research Award) granted to JS.

Additional information

Funding

This work was supported by a Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery grant awarded to EKJ, a SSHRC grant awarded to EKJ, and an NSERC USRA (Undergraduate Student Research Award) granted to JS.