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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 18 of 18 1 How Efficiency Shapes Human Language Gibson, Edward; Futrell, Richard; Piantadosi, Steven... In: https://hal.archives-ouvertes.fr/hal-03552539 ; 2022 (2022) BASE Show details 2 Functional pressures and linguistic typology Meinhardt, Eric. - : eScholarship, University of California, 2021 BASE Show details 3 An ERP index of real-time error correction within a noisy-channel framework of human communication. Ryskin, Rachel; Stearns, Laura; Bergen, Leon. - : eScholarship, University of California, 2021 BASE Show details 4 An ERP index of real-time error correction within a noisy-channel framework of human communication Ryskin, Rachel; Stearns, Laura; Bergen, Leon... In: bioRxiv (2021) BASE Show details 5 Speakers Enhance Contextually Confusable Words Meinhardt, Eric; Bakovic, Eric; Bergen, Leon. - : eScholarship, University of California, 2020 BASE Show details 6 Word Frequency Does Not Predict Grammatical Knowledge in Language Models ... Yu, Charles; Sie, Ryan; Tedeschi, Nico. - : arXiv, 2020 BASE Show details 7 How Efficiency Shapes Human Language ; How Efficiency Shapes Human Language, TICS 2019 Gibson, Edward A; Futrell, Richard; Piantadosi, Steven... In: Prof. Levy via Courtney Crummett (2019) BASE Show details 8 Color naming across languages reflects color use Ratnasingam, Sivalogeswaran; Piantadosi, Steven T.; Conway, Bevil R.... In: National Academy of Sciences (2018) BASE Show details 9 Learning Structured Preferences Bergen, Leon; Evans, Owain Rhys; Tenenbaum, Joshua B In: Other univ. web domain (2017) BASE Show details 10 Color naming across languages reflects color use Gibson, Edward; Futrell, Richard; Jara-Ettinger, Julian. - : National Academy of Sciences, 2017 BASE Show details 11 Joint inference in pragmatic reasoning Bergen, Leon. - : Massachusetts Institute of Technology, 2016 BASE Show details 12 Processing temporal presuppositions: an event-related potential study Stearns, Laura; Eddy, Marianna; Jouravlev, Olessia... In: Prof. Gibson via Courtney Crummett (2016) BASE Show details 13 Processing temporal presuppositions: an event-related potential study ... Jouravlev, Olessia; Stearns, Laura; Bergen, Leon. - : Taylor & Francis, 2016 BASE Show details 14 Processing temporal presuppositions: an event-related potential study ... Jouravlev, Olessia; Stearns, Laura; Bergen, Leon. - : Taylor & Francis, 2016 BASE Show details 15 A rational inference approach to aphasic language comprehension Sandberg, Chaleece; Fedorenko, Evelina; Kiran, Swathi... In: Prof. Gibson via Courtney Crummett (2015) BASE Show details 16 Nonliteral understanding of number words Bergen, Leon; Kao, Justine T.; Wu, Jean Y.... In: National Academy of Sciences (U.S.) (2014) BASE Show details 17 Rational integration of noisy evidence and prior semantic expectations in sentence interpretation Gibson, Edward; Bergen, Leon; Piantadosi, Steven T.. - : National Academy of Sciences, 2013 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. Keyword: Social Sciences URL: http://www.ncbi.nlm.nih.gov/pubmed/23637344 https://doi.org/10.1073/pnas.1216438110 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3657782 BASE Hide details 18 Rational integration of noisy evidence and prior semantic expectations in sentence interpretation Gibson, Edward A.; Bergen, Leon; Piantadosi, Steven T. In: PNAS (2012) BASE Show details

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