Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7807
Title: Short-term and working memory capacity and the language device: Chunking and parsing complexity
Authors: Lu, Bingfu 
Prof. WEN Zhisheng, Edward 
Issue Date: 2022
Publisher: Cambridge: Cambridge University Press.
Source: In John Schwieter & Wen, Zhisheng. (eds.) 2022. The Cambridge handbook of working memory and language (pp. 393-417). Cambridge: Cambridge University Press.
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 visà-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.
Type: Book Chapter
URI: http://hdl.handle.net/20.500.11861/7807
Appears in Collections:English Language & Literature - Publication

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