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18 - Short-Term and Working Memory Capacity and the Language Device

Chunking and Parsing Complexity

from Part III - Linguistic Theories and Frameworks

Published online by Cambridge University Press:  08 July 2022

By
Bingfu Lu  and
Zhisheng (Edward) Wen
Edited by
John W. Schwieter  and
Zhisheng (Edward) Wen
John W. Schwieter
Affiliation:
Wilfrid Laurier University
Zhisheng (Edward) Wen
Affiliation:
Hong Kong Shue Yan University
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Summary

Many general linguistic theories and language processing frameworks have assumed that language processing is largely a chunking procedure and that it is underpinned and constrained by our memory limitations. Despite this general consensus, the distinction between short-term memory (STM) and working memory (WM) limitations as they relate to language processing has remained elusive. To resolve this issue, we propose an integrated memory- and chunking-based metric of parsing complexity, in which STM limitations of 7 ± 2 (Miller, 1956a) are relevant to the Momentary Chunk Number (MCN), while WM limitations of 4 ± 1 (Cowan, 2001) are relevant to the Mean Momentary Chunk Number (MMCN). Examples of concrete calculations of our new metric are presented vis-à-vis Liu’s MDD metric and Hawkins’ IC-to-word Ratio metric. Related methodology issues are also discussed. We conclude the paper by echoing some recently repeated calls -(O'Grady, 2012 & 2017; Gómez-Rodríguez et al., 2019; Wen, 2019) to include STM and WM limitations as part and parcel of the language device (LD; cf. Chomsky, 1957) in that their impacts are ubiquitous and permeating in all essential linguistic domains ranging from phonology to grammar, discourse comprehension and production.

Keywords

memory capacityshort-term memory limitationsworking memory limitationsthe magical number 7chunkingMomentary Chunk Number (MCN)Mean MCN (MMCN)Mean Dependency Distance (MDD)Word/IC ratioparsing complexitythe language device
Type
Chapter
Information
The Cambridge Handbook of Working Memory and Language , pp. 393 - 418
Publisher: Cambridge University Press
Print publication year: 2022

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