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Short-term and working memory capacity and the language device: Chunking and parsing complexity

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. (PDF) Short-term and working memory capacity and the language device: Chunking and parsing complexity. Available from: https://www.researchgate.net/publication/340490956_Short-term_and_working_memory_capacity_and_the_language_device_Chunking_and_parsing_complexity [accessed May 31 2021].