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From partners to populations: A hierarchical Bayesian account of coordination and convention ...
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Shades of confusion: Lexical uncertainty modulates ad hoc coordination in an interactive communication task ...
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Evaluating Models of Robust Word Recognition with Serial Reproduction ...
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Abstract:
Spoken communication occurs in a "noisy channel" characterized by high levels of environmental noise, variability within and between speakers, and lexical and syntactic ambiguity. Given these properties of the received linguistic input, robust spoken word recognition -- and language processing more generally -- relies heavily on listeners' prior knowledge to evaluate whether candidate interpretations of that input are more or less likely. Here we compare several broad-coverage probabilistic generative language models in their ability to capture human linguistic expectations. Serial reproduction, an experimental paradigm where spoken utterances are reproduced by successive participants similar to the children's game of "Telephone," is used to elicit a sample that reflects the linguistic expectations of English-speaking adults. When we evaluate a suite of probabilistic generative language models against the yielded chains of utterances, we find that those models that make use of abstract representations of ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.2101.09788 https://arxiv.org/abs/2101.09788
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Generalizing meanings from partners to populations: Hierarchical inference supports convention formation on networks ...
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Investigating representations of verb bias in neural language models ...
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Intuitive Theories as Grammars for Causal Inference
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In: MIT web domain (2019)
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Learning Hierarchical Visual Representations in Deep Neural Networks Using Hierarchical Linguistic Labels ...
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Word forms - not just their lengths- are optimized for efficient communication ...
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The Hierarchical Cortical Organization of Human Speech Processing
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Natural speech reveals the semantic maps that tile human cerebral cortex.
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In: Nature, vol 532, iss 7600 (2016)
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The Sapir-Whorf Hypothesis and Probabilistic Inference: Evidence from the Domain of Color
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In: Cibelli, Emily; Xu, Yang; Austerweil, Joseph L; Griffiths, Thomas L; & Regier, Terry. (2016). The Sapir-Whorf Hypothesis and Probabilistic Inference: Evidence from the Domain of Color. PLOS ONE, 11(7), e0158725. doi:10.1371/journal.pone.0158725. UC Berkeley: UC Berkeley Library. Retrieved from: http://www.escholarship.org/uc/item/1pt8b5dj (2016)
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The Sapir-Whorf Hypothesis and Probabilistic Inference: Evidence from the Domain of Color.
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In: PloS one, vol 11, iss 7 (2016)
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The Sapir-Whorf Hypothesis and Probabilistic Inference: Evidence from the Domain of Color
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Natural speech reveals the semantic maps that tile human cerebral cortex
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