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Russell Richie

Researcher at University of Pennsylvania

Publications -  25
Citations -  337

Russell Richie is an academic researcher from University of Pennsylvania. The author has contributed to research in topics: Computer science & Natural language. The author has an hindex of 7, co-authored 19 publications receiving 219 citations. Previous affiliations of Russell Richie include Children's Hospital of Philadelphia & Temple University.

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Babies Catch a Break 7- to 9-Month-Olds Track Statistical Probabilities in Continuous Dynamic Events

TL;DR: This study familiarized infants to a corpus of dynamic, continuous events and tested their ability to differentiate units from part-units, paralleled that of research showing that infants utilize transitional probabilities in a Corpus of natural speech and use statistics to distinguish words from parts-words.
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Converging evidence: Network structure effects on conventionalization of gestural referring expressions

TL;DR: A silent gesture paradigm is used that combines the methodological control of experimental semiotics and computational simulations with the naturalistic affordances of the human body, physical environment, and interpersonal communication to demonstrate greater conventionalization among participants in the richly-connected condition.
Journal Article

Modeling the Emergence of Lexicons in Homesign Systems.

TL;DR: This work shows conventionalization of lexicons in two different classes of naturally emerging signed systems, and model conventionalization as a population of interacting individuals who adjust their probability of sign use in response to other individuals' actual sign use, following an independently motivated model of language learning.
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Modeling the Emergence of Lexicons in Homesign Systems

TL;DR: This paper investigated the role of community structure in the emergence of linguistic conventions with both naturalistic empirical data and computational modeling, and found that a richer social network, like that of natural (signed) languages, conventionalizes faster than a sparser social network.
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Distributed semantic representations for modeling human judgment

TL;DR: This work focuses on distributed semantic representations, a key component of computational models that represent knowledge, make evaluations and attributions, and give responses, in a human-like manner, for high-level judgments.