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Low-dimensional representation of infant and adult vocalization acoustics ...
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Additional Results and details of "On the physical origin of linguistic laws and lognormality in speech" ...
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Additional Results and details of "On the physical origin of linguistic laws and lognormality in speech" ...
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Supplementary material from "On the physical origin of linguistic laws and lognormality in speech" ...
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Supplementary material from "On the physical origin of linguistic laws and lognormality in speech" ...
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On the physical origin of linguistic laws and lognormality in speech
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A neural network model of the articulatory-acoustic forward mapping trained on recordings of articulatory parameters. ...
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Supplementary material from "Hierarchical temporal structure in music, speech and animal vocalizations: jazz is like a conversation, humpbacks sing like hermit thrushes" ...
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Supplementary material from "Hierarchical temporal structure in music, speech and animal vocalizations: jazz is like a conversation, humpbacks sing like hermit thrushes" ...
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Hierarchical temporal structure in music, speech and animal vocalizations: jazz is like a conversation, humpbacks sing like hermit thrushes
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The segment as the minimal planning unit in speech production and reading aloud: evidence and implications.
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The segment as the minimal planning unit in speech production and reading aloud: evidence and implications
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Walking across Wikipedia: a scale-free network model of semantic memory retrieval.
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In: Frontiers in psychology, vol 5, iss FEB (2014)
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Abstract:
Semantic knowledge has been investigated using both online and offline methods. One common online method is category recall, in which members of a semantic category like "animals" are retrieved in a given period of time. The order, timing, and number of retrievals are used as assays of semantic memory processes. One common offline method is corpus analysis, in which the structure of semantic knowledge is extracted from texts using co-occurrence or encyclopedic methods. Online measures of semantic processing, as well as offline measures of semantic structure, have yielded data resembling inverse power law distributions. The aim of the present study is to investigate whether these patterns in data might be related. A semantic network model of animal knowledge is formulated on the basis of Wikipedia pages and their overlap in word probability distributions. The network is scale-free, in that node degree is related to node frequency as an inverse power law. A random walk over this network is shown to simulate a number of results from a category recall experiment, including power law-like distributions of inter-response intervals. Results are discussed in terms of theories of semantic structure and processing.
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Keyword:
category recall; Cognitive Sciences; levy foraging; Psychology; scale-free network; semantics
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URL: https://escholarship.org/uc/item/3338d3d9
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Walking across Wikipedia: a scale-free network model of semantic memory retrieval
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