The remarkable inefficiency of word recognition
By Denis G. Pelli, B. Farell, Deborah C. Moore. Nature, 2003
306 citations recorded by the source corpus.
Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology
View Paper: https://www.semanticscholar.org/paper/2521143c64ac549850c7a7e4e843c4be0c7673d3
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cognitive Neuroscience
- Stanislas Dehaene
- Leonardo G. Cohen
- Colin J. Davis
- Jeffrey S. Bowers
- Dennis Norris
- John K. Tsotsos
- Yonatan Belinkov
- Alexander Andreopoulos
In Experimental and Cognitive Psychology
- Colin J. Davis
- Stanislas Dehaene
- Leonardo G. Cohen
- Jeffrey S. Bowers
- Dennis Norris
- Yonatan Belinkov
- Yonatan Bisk
- Cathy J. Price
Citations in the corpus
- Bayesian just-so stories in psychology and neuroscience. (2012, background): “For evidence regarding the " remarkable inefficiency " of visual word identification, see Pelli, Farell, and Moore (2003).”
- Specialization within the ventral stream: the case for the visual word form area (2004, background): “Finally, the functional visual units that are represented in this region beyond the level of individual letters are still a matter of research (Pelli et al., 2003).”
- 50 Years of object recognition: Directions forward (2013, result): “[103] provide some compelling arguments in support of the parts based approach.”
- Visual Word Recognition (2007, unknown): “Though this hypothesis continues to engender fascination (e.g. Pelli et al., 2003; Perea and Rosa, 2002; Saenger, 1997), most modern theories suggest that word recognition is based on the analysis of letters.”
- Synthetic and Natural Noise Both Break Neural Machine Translation (2017, methodology): “, 1997), that we can switch between whole word recognition and piecing together words from letters (Reicher, 1969; Pelli et al., 2003), and there appears to be no evidence that the first and last letter positions are required to stay constant for comprehension.”
- The Bayesian reader: explaining word recognition as an optimal Bayesian decision process. (2006, methodology): “Pelli et al. (2003) simulated their data using a two-stage model in which the first stage outputs a single hypothesis as to the identity of each letter.”