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Towards a network model of the articulatory loop.

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Towards a network model of the articulatory loop. / Burgess, N.; Hitch, G. J.
In: Journal of Memory and Language, Vol. 31, No. 4, 1992, p. 429-460.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Burgess, N & Hitch, GJ 1992, 'Towards a network model of the articulatory loop.', Journal of Memory and Language, vol. 31, no. 4, pp. 429-460. https://doi.org/10.1016/0749-596X(92)90022-P

APA

Vancouver

Burgess N, Hitch GJ. Towards a network model of the articulatory loop. Journal of Memory and Language. 1992;31(4):429-460. doi: 10.1016/0749-596X(92)90022-P

Author

Burgess, N. ; Hitch, G. J. / Towards a network model of the articulatory loop. In: Journal of Memory and Language. 1992 ; Vol. 31, No. 4. pp. 429-460.

Bibtex

@article{fcd46fe68ae8491dbf94c62eb6f51f9e,
title = "Towards a network model of the articulatory loop.",
abstract = "The basic features of verbal short-term memory for serially ordered lists are reviewed. A feed-forward network model based on Baddeley's concept of an “articulatory loop” is presented. One of its aims was to explore mechanisms for the storage of serial order information in the articulatory loop. Information is represented locally, learning is by “one-shot” Hebbian adjustment of weighted connections, corresponding to item-item and item-context associations, which decay with time. Items are modeled at the level of phonemes and phonemic output is fed back to the next phonemic input. At recall, items are selected serially by “competitive queuing.” Noisy activation values are used, resulting in errors during recall. Simulations of recall showed good agreement with human performance with respect to memory span, phonemic similarity, word length, and patterns of error. There was good but incomplete agreement on the shape of the serial position curve and on the effects of articulatory suppression. A simple modification is shown to produce the correct serial position curve. However, the model was unable to simulate human memory for sequences containing mixtures of phonemically similar and dissimilar items. A suggested modification which retains the central idea of using competitive queuing to select among noisy activation values is described.",
author = "N. Burgess and Hitch, {G. J.}",
year = "1992",
doi = "10.1016/0749-596X(92)90022-P",
language = "English",
volume = "31",
pages = "429--460",
journal = "Journal of Memory and Language",
publisher = "Academic Press Inc.",
number = "4",

}

RIS

TY - JOUR

T1 - Towards a network model of the articulatory loop.

AU - Burgess, N.

AU - Hitch, G. J.

PY - 1992

Y1 - 1992

N2 - The basic features of verbal short-term memory for serially ordered lists are reviewed. A feed-forward network model based on Baddeley's concept of an “articulatory loop” is presented. One of its aims was to explore mechanisms for the storage of serial order information in the articulatory loop. Information is represented locally, learning is by “one-shot” Hebbian adjustment of weighted connections, corresponding to item-item and item-context associations, which decay with time. Items are modeled at the level of phonemes and phonemic output is fed back to the next phonemic input. At recall, items are selected serially by “competitive queuing.” Noisy activation values are used, resulting in errors during recall. Simulations of recall showed good agreement with human performance with respect to memory span, phonemic similarity, word length, and patterns of error. There was good but incomplete agreement on the shape of the serial position curve and on the effects of articulatory suppression. A simple modification is shown to produce the correct serial position curve. However, the model was unable to simulate human memory for sequences containing mixtures of phonemically similar and dissimilar items. A suggested modification which retains the central idea of using competitive queuing to select among noisy activation values is described.

AB - The basic features of verbal short-term memory for serially ordered lists are reviewed. A feed-forward network model based on Baddeley's concept of an “articulatory loop” is presented. One of its aims was to explore mechanisms for the storage of serial order information in the articulatory loop. Information is represented locally, learning is by “one-shot” Hebbian adjustment of weighted connections, corresponding to item-item and item-context associations, which decay with time. Items are modeled at the level of phonemes and phonemic output is fed back to the next phonemic input. At recall, items are selected serially by “competitive queuing.” Noisy activation values are used, resulting in errors during recall. Simulations of recall showed good agreement with human performance with respect to memory span, phonemic similarity, word length, and patterns of error. There was good but incomplete agreement on the shape of the serial position curve and on the effects of articulatory suppression. A simple modification is shown to produce the correct serial position curve. However, the model was unable to simulate human memory for sequences containing mixtures of phonemically similar and dissimilar items. A suggested modification which retains the central idea of using competitive queuing to select among noisy activation values is described.

U2 - 10.1016/0749-596X(92)90022-P

DO - 10.1016/0749-596X(92)90022-P

M3 - Journal article

VL - 31

SP - 429

EP - 460

JO - Journal of Memory and Language

JF - Journal of Memory and Language

IS - 4

ER -