It is Not What You Say but How You Say It: Evidence from Russian Shows Robust Effects of the Structural Prior on Noisy Channel Inferences.
JOURNAL OF EXPERIMENTAL PSYCHOLOGY-LEARNING MEMORY AND COGNITION(2024)
MIT | Univ Calif Merced | Stanford Univ
Abstract
Under the noisy-channel framework of language comprehension, comprehenders infer the speaker's intended meaning by integrating the perceived utterance with their knowledge of the language, the world, and the kinds of errors that can occur in communication. Previous research has shown that, when sentences are improbable under the meaning prior (implausible sentences), participants often interpret them nonliterally. The rate of nonliteral interpretation is higher when the errors that could have transformed the intended utterance into the perceived utterance are more likely. However, previous experiments on noisy channel processing mostly relied on implausible sentences, and it is unclear whether participants' nonliteral interpretations were evidence of noisy channel processing or the result of trying to conform to the experimenter's expectations in an experiment with nonsensical sentences. In the current study, we used the unique properties of Russian, an understudied language in the psycholinguistics literature, to test noisy-channel comprehension using only simple plausible sentences. The prior plausibility of sentences was tied only to their word order; subject-verb-object (SVO) sentences were more probable under the structural prior than object-verb-subject (OVS) sentences. In two experiments, we show that participants often interpret OVS sentences nonliterally, and the probability of nonliteral interpretations depended on the Levenshtein distance between the perceived sentence and the (potentially intended) SVO version of the sentence. The results show that the structural prior guides people's final interpretation, independent of the presence of semantic implausibility. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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Key words
sentence processing,noisy channel processing,structural prior,Russian
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