Parsing as a Cue‐Based Retrieval Model

Abstract This paper develops a novel psycholinguistic parser and tests it against experimental and corpus reading data. The parser builds on the recent research into memory structures, which argues that memory retrieval is content‐addressable and cue‐based. It is shown that the theory of cue‐based memory systems can be combined with transition‐based parsing to produce a parser that, when combined with the cognitive architecture ACT‐R, can model reading and predict online behavioral measures (reading times and regressions). The parser's modeling capacities are tested against self‐paced reading experimental data (Grodner & Gibson, 2005), eye‐tracking experimental data (Staub, 2011), and a self‐paced reading corpus (Futrell et al., 2018).

• Publication year

  2021

• Venue

  Cognitive Sciences

• Publication date

  2021-08-01

• Fields of study

  Medicine, Linguistics, Computer Science, Psychology

• Identifiers
  DOI 10.1111/cogs.13020PMID 34379334PMCID 8459291
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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