This week at MCQLL, Michaela Socolof will lead a discussion on the paper “A noisy-channel model of rational human sentence comprehension under uncertain input” by Roger Levy (abstract below). The setup will be somewhat different from the typical MCQLL presentations. Michaela will have some discussion topics prepared for the group, please give the paper a read before the meeting to make the discussion more dynamic!

As usual the meeting is from 14:30-16:00 on Wednesday. A late lunch will be provided.

Abstract: Language comprehension, as with all other cases of the extraction of meaningful structure from perceptual input, takes places under noisy conditions. If human language comprehension is a rational process in the sense of making use of all available information sources, then we might expect uncertainty at the level of word-level input to affect sentence-level comprehension. However, nearly all contemporary models of sentence comprehension assume clean input—that is, that the input to the sentence-level comprehension mechanism is a perfectly-formed, completely certain sequence of input tokens (words). This article presents a simple model of rational human sentence comprehension under noisy input, and uses the model to investigate some outstanding problems in the psycholinguistic literature for theories of rational human sentence comprehension. We argue that by explicitly accounting for input level noise in sentence processing, our model provides solutions for these outstanding problems and broadens the scope of theories of human sentence comprehension as rational probabilistic inference.

Link to the paper: