Rational integration of noisy evidence and prior semantic expectations in sentence interpretation

Abstract

Sentence processing theories typically assume that the input to our language processing mechanisms is an error-free sequence of words. However, this assumption is an oversimplification because noise is present in typical language use (for instance, due to a noisy environment, producer errors, or perceiver errors). A complete theory of human sentence comprehension therefore needs to explain how humans understand language given imperfect input. Indeed, like many cognitive systems, language processing mechanisms may even be "well designed"-in this case for the task of recovering intended meaning from noisy utterances. In particular, comprehension mechanisms may be sensitive to the types of information that an idealized statistical comprehender would be sensitive to. Here, we evaluate four predictions about such a rational (Bayesian) noisy-channel language comprehender in a sentence comprehension task: (i) semantic cues should pull sentence interpretation towards plausible meanings, especially if the wording of the more plausible meaning is close to the observed utterance in terms of the number of edits; (ii) this process should asymmetrically treat insertions and deletions due to the Bayesian "size principle"; such nonliteral interpretation of sentences should (iii) increase with the perceived noise rate of the communicative situation and (iv) decrease if semantically anomalous meanings are more likely to be communicated. These predictions are borne out, strongly suggesting that human language relies on rational statistical inference over a noisy channel.T raditionally, models of sentence comprehension have assumed that the input to the sentence comprehension mechanism is an error-free sequence of words (e.g., refs. 1-6). However, the noise inherent in normal language use-due to producer or perceiver errors-makes this assumption an oversimplification. For example, language producers may misspeak or mistype because they do not have a full command of the language (due to being very young or a nonnative speaker, or suffering from a language disorder like aphasia), because they have not fully planned an utterance in advance, or because they are trying to communicate under the influence of stress or confusion. Similarly, language comprehenders may mishear or misread things because of their own handicaps (e.g., poor hearing/sight, or not paying sufficient attention), because the environment is noisy, or because the producer is not making sufficient effort in communicating clearly (e.g., whispering or mumbling, or writing in sloppy handwriting). Given the prevalence of these noise sources, it is plausible that language processing mechanisms are well adapted to handling noisy input, and so a complete model of language comprehension must allow for the existence of noise.Noisy-channel models (7) of speech perception have been prominent in the literature for many years (e.g., 8-11). Furthermore, several researchers have observed the importance of noise in the input for the compositional, syntactic processes of sentence unders...

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