Object identification difficulty can be predicted based on disfluencies and eye-movements in connected speech

To reveal the underlying cause of disfluency, several authors use a network task, where participants describe the route taken by a marker through visually presented networks of objects. To be able to disentangle disfluency related to word preparation from other factors, we combined this task with eye-tracking. We asked whether delays in the earliest stages of picture naming elicit disfluency. We therefore used visual blurring which hinders visual identification of the items and thereby slows down selection of a lexical concept. This manipulation did not lead to more disfluency on average and viewing times decreased with blurred pictures. However, multivariate pattern analyses revealed that a classifier could predict, from the pattern of disfluency, whether each participant was about to name blurred or control pictures. Impeding the conceptual generation of a message therefore affected the pattern of disfluencies of each participant individually, but this pattern was not consistent from one participant to another.