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Short-Term and Working Memory Capacity and the Language Device: Chunking and Parsing Complexity

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

4 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationThe Cambridge Handbook of Working Memory and Language
PublisherCambridge University Press
Pages393-418
Number of pages26
ISBN (Electronic)9781108955638
ISBN (Print)9781108845342
DOIs
Publication statusPublished - 21 Jul 2022

Keywords

  • chunking
  • Mean Dependency Distance (MDD)
  • Mean MCN (MMCN)
  • memory capacity
  • Momentary Chunk Number (MCN)
  • parsing complexity
  • short-term memory limitations
  • the language device
  • the magical number 7
  • Word/IC ratio
  • working memory limitations

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