The word segmentation process as revealed by click detection

The click detection paradigm was once conceived as a method to study online syntactic processing, but well-controlled empirical investigations casted many doubts on the early findings based on it. In this paper, we show that click methods can still prove valid and useful. We asked adult participants to listen to an artificial speech stream composed of statistically defined trisyllabic nonce words, while having to detect clicks superposed on the stream. The clicks were presented either within or between consecutive words. After 2 minutes of exposure to the stream, participants were slower to detect clicks located within words than clicks located between words. This result suggests that methods like click detection are sensitive to online statistical computations, opening new possibilities to obtain a richer picture of the segmentation process than what was hitherto possible.