Prediction in Language Processing
There is strong evidence that human sentence processing is incremental, i.e., that structures are built word by word. Recent experimental results show that the processor us also predictive, i.e., it can anticipate upcoming linguistic material on the basis of previous input. However, the granularity of this prediction process is currently unclear. We present evidence from two visual world experiments that show that speakers can make fine-grained predictions based on the frame and the frequency of a verb. We use this data to motivate a computational model of human parsing that includes an explicit mechanism for generating and verifying predictions. Based on this mechanism, our model can capture both locality effects and surprisal effects, and thus unify a body of empirical results that have so far been accounted separately.
