Fixation durations in first-pass reading reflect uncertainty about word identity

Fixation durations in first-pass reading reflect uncertainty about word identity Nathaniel J. Smith njsmith@cogsci.ucsd. edu UC San Diego Department of Cognitive Science 9500 Gilman Drive #515, La Jolla, CA 92093-0515 USA Roger Levy rlevy@ling.ucsd. edu UC San Diego Department of Linguistics 9500 Gilman Drive #108, La Jolla, CA 92093-0108 USA Abstract In reading, it is often assumed that words are recognized suf- ficiently quickly, accurately, and unambiguously that down- stream processes may proceed with perfect information about word identity. For example, word predictability is believed to affect early reading time measures, yet a word’s predictability cannot be calculated without knowledge of the word’s identity. We argue that such information is not, in general, available to the language processing system, and that it proceeds with only probabilistic information about word identity. We pre- dict therefore that what have been analyzed previously as pre- dictability effects must instead be based on noisy estimates of word predictability that are influenced by the predictability of visually similar words (neighbors). We test this prediction by building a Bayesian model of visual word recognition, using it to compute the ‘average neighborhood surprisal’ of words in a corpus, and testing the ability of this novel measure to explain human reading time data. Keywords: Psychology, Cognitive Science, Perception, Lan- guage Understanding, Bayesian Modeling, Neighborhood Ef- fects, Visual Uncertainty, Reading Performance in isolated word recognition tasks is often af- fected by the existence or properties of words that are not presented, but that are visually similar to the words which are presented. For instance, a word with many neighbors — especially high frequency neighbors — tends to produce a faster response in the lexical decision task, and a slower response in naming or reading tasks (Perea & Rosa, 2000). Norris (2006) has argued that these divergent results can be best explained by uncertainty in the processing system. That is, noise is an inevitable component of all biological compu- tation, and if the processor receives only noisy information about a word’s shape, then it must consider all similar look- ing words as candidates for identification. When there are many such candidates, identifying the single correct candi- date (as in the naming task) becomes more difficult, because there are many incorrect distractors and only one correct tar- get; resolving this difficulty requires the acquisition of more sensory information, which requires more time. In the lexical decision task, however, it is not necessary to determine which word is seen, only whether a word is seen, and therefore in- creasing the number of candidates only makes it easier to give a correct response (even if for the ‘wrong’ reason). However, in reading — that is, processing connected lan- guage, rather than isolated words — another consideration arises. In a naming task, no response can be given until the word is identified, but when reading, the ultimate outcome is not the name of a single word, but an understanding of the text as a whole. Here, we ask: can the linguistic processing associated with a word proceed before that word is uniquely identified? And if so, what are the consequences for pro- cessing? It’s possible that neighborhood effects are limited to some early, serial, word identification process, in which any uncertainty is resolved before higher-level linguistic pro- cesses begin. Alternatively, this uncertainty may be propa- gated through the linguistic processing system itself. Most current models of high-level language processing fall into the former category; for instance, they take as input words, rather than probability distributions over words. How- ever, there is some reason to suspect that the latter possibility is more plausible. Spoken language, in particular, is a very noisy signal, in which word identification is generally im- possible without reference to high-level linguistic constraints. Furthermore, listeners are willing to revise their identifica- tion of perceptually ambiguous phonetic material in light of disambiguating material that follows within a short period (Connine, Blasko, & Hall, 1991). In reading, the availabil- ity of a stable visual record makes it possible in principle to acquire substantially more detailed perceptual information — but in practice the average fixation length in reading is 200 ms, comparable to the time required to plan a motor saccade. This suggests that the next saccade must be initiated almost as soon as the fixation begins, and that decisions about its timing — and thus the fixation time for the current word — must be made before the current word is fully processed. In addition, Levy, Bicknell, Slattery, and Rayner (2009) have recently used evidence from a reading task to argue that cer- tain syntactic constructions associated with garden-path-like processing difficulty may arise from uncertainty about the identity of critical words earlier in the sentence. Therefore it seems plausible that the language processing system not only has the capacity to handle uncertain input, but that this ability is used in natural reading. Here, we examine this question via the well-known effect of word predictability on reading time (predictable words are read more quickly, Ehrlich & Rayner, 1981). This is a useful tool, because (i) the effect is very early; it affects the duration of initial fixations on a word, in the 200–300 ms range, when we would most expect some uncertainty to remain, and (ii)