Data from eye-tracking corpora as evidence for theories of syntactic processing complexity.

By Vera Demberg, Frank Keller. Cognition, 2008

651 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Cognitive Neuroscience, Developmental and Educational Psychology

View Paper: https://www.semanticscholar.org/paper/41215599674d8a81e7420f2a40320868f3dbc2f1

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Citations in the corpus

Composition in Distributional Models of Semantics (2010, background): “Another interesting application concerns sentence processing and the extent to which the compositional models discussed here can explain reading times in eye-tracking corpora (Demberg & Keller, 2008; Pynte, New, & Kennedy, 2008).”
The Extended SPaRKy Restaurant Corpus: Designing a Corpus with Variable Information Density (2017, background): “In written text, for example, we know that information density significantly influences processing difficulty [11] in reading.”
Investigating locality effects and surprisal in written English syntactic choice phenomena. (2016, positive): “…(n-gram log probability, latent variable PCFG surprisal and embedding depth measures) proposed in the computational psycholinguistics literature (Demberg & Keller 2008, Roark, Bachrach, Cardenas, & Pallier 2009, Wu et al. 2010), in particular for various postverbal syntactic choice alternations.”
What do we mean by prediction in language comprehension? (2015, background): “…Ehrlich & Rayner, 1981; Rayner, Binder, Ashby, & Pollatsek, 2001; Rayner & Well, 1996; see also Boston, Hale, Kliegl, Patil, & Vasishth, 2008; Demberg & Keller, 2008; Demberg, Keller, & Koller, 2013; Frank & Bod, 2011; McDonald & Shillcock, 2003; Smith & Levy, 2013; see Staub, 2015 for a…”
Cognitively Plausible Models of Human Language Processing (2010, methodology): “Some relevant corpora have already been constructed, see the overview in Table 3, and various authors have used them for model evaluation (Demberg and Keller, 2008a; Pynte et al., 2008; Frank, 2009; Ferrara Boston et al., 2008; Patil et al., 2009; Roark et al., 2009; Mitchell et al., 2010).”
Statistical Measures for Usage‐Based Linguistics (2015, background): “…(Clark, 2013; Rescorla & Wagner, 1972; Rumelhart, Hinton, & Williams, 1986; Wills, 2009), and there is increasing evidence for surprisal-driven language processing and acquisition (Dell & Chang, in press; Demberg & Keller, 2008; Jaeger & Snider, 2013; Pickering & Garrod, 2013; Smith & Levy, 2013).”
The effect of word predictability on reading time is logarithmic (2013, positive): “Previous work (Demberg & Keller, 2008; Frank & Bod, 2011; Kennedy, Pynte, Murray, & Paul, in press) has reported predictability effects in this corpus, but did not examine curve shape.”
The statistical significance filter leads to overoptimistic expectations of replicability (2018, positive): “There is compelling evidence consistent with the expectation-based account proposed by Levy (2008) (some examples are the work of Demberg & Keller, 2008; Kwon, Lee, Gordon, Kluender, & Polinsky, 2010; Linzen & Jaeger, 2016).”
Zipf’s word frequency law in natural language: A critical review and future directions (2014, background): “…means that a theory based on communication should be intrinsically linked to theories of what human language comprehenders find predictable (e.g. Demberg & Keller, 2008; A. Frank & Jaeger, 2008; Jaeger, 2010; Levy, 2008; Levy & Jaeger, 2007; Piantadosi, Tily, & Gibson, 2011; N. J. Smith & Levy,…”
Assessing Relative Sentence Complexity using an Incremental CCG Parser (2016, background): “…parsing has shown to be useful for many real-time applications such as language modeling for speech recognition (Chelba and Jelinek, 2000; Roark, 2001), modeling text reading time (Demberg and Keller, 2008), dialogue systems (Stoness et al., 2004) and machine translation (Schwartz et al., 2011).”