SP-EyeGAN: Generating Synthetic Eye Movement Data with Generative Adversarial Networks

Neural networks that process the raw eye-tracking signal can outperform traditional methods that operate on scanpaths preprocessed into fixations and saccades. However, the scarcity of such data poses a major challenge. We, therefore, present SP-EyeGAN, a neural network that generates synthetic raw eye-tracking data. SP-EyeGAN consists of Generative Adversarial Networks; it produces a sequence of gaze angles indistinguishable from human micro- and macro-movements. We demonstrate how the generated synthetic data can be used to pre-train a model using contrastive learning. This model is fine-tuned on labeled human data for the task of interest. We show that for the task of predicting reading comprehension from eye movements, this approach outperforms the previous state-of-the-art

How strongly do word reading times and lexical decision times correlate? Combining data from eye movement corpora and megastudies

We assess the amount of shared variance between three measures of visual word recognition latencies: eye movement latencies, lexical decision times and naming times. After partialling out the effects of word frequency and word length, two well-documented predictors of word recognition latencies, we see that 7-44% of the variance is uniquely shared between lexical decision times and naming times, depending on the frequency range of the words used. A similar analysis of eye movement latencies shows that the percentage of variance they uniquely share either with lexical decision times or with naming times is much lower. It is 5 – 17% for gaze durations and lexical decision times in studies with target words presented in neutral sentences, but drops to .2% for corpus studies in which eye movements to all words are analysed. Correlations between gaze durations and naming latencies are lower still. These findings suggest that processing times in isolated word processing and continuous text reading are affected by specific task demands and presentation format, and that lexical decision times and naming times are not very informative in predicting eye movement latencies in text reading once the effect of word frequency and word length are taken into account. The difference between controlled experiments and natural reading suggests that reading strategies and stimulus materials may determine the degree to which the immediacy-of-processing assumption and the eye-mind assumption apply. Fixation times are more likely to exclusively reflect the lexical processing of the currently fixated word in controlled studies with unpredictable target words rather than in natural reading of sentences or texts

Predicting Native Language from Gaze

A fundamental question in language learning concerns the role of a speaker's first language in second language acquisition. We present a novel methodology for studying this question: analysis of eye-movement patterns in second language reading of free-form text. Using this methodology, we demonstrate for the first time that the native language of English learners can be predicted from their gaze fixations when reading English. We provide analysis of classifier uncertainty and learned features, which indicates that differences in English reading are likely to be rooted in linguistic divergences across native languages. The presented framework complements production studies and offers new ground for advancing research on multilingualism.Comment: ACL 201

Eye movements in code reading:relaxing the linear order

Abstract—Code reading is an important skill in programming. Inspired by the linearity that people exhibit while natural lan-guage text reading, we designed local and global gaze-based mea-sures to characterize linearity (left-to-right and top-to-bottom) in reading source code. Unlike natural language text, source code is executable and requires a specific reading approach. To validate these measures, we compared the eye movements of novice and expert programmers who were asked to read and comprehend short snippets of natural language text and Java programs. Our results show that novices read source code less linearly than natural language text. Moreover, experts read code less linearly than novices. These findings indicate that there are specific differences between reading natural language and source code, and suggest that non-linear reading skills increase with expertise. We discuss the implications for practitioners and educators. I

The Relations Between Children's Comprehension Monitoring and Their Reading Comprehension and Vocabulary Knowledge: An Eye-Movement Study.

Poor reading comprehension may be due to having ineffective comprehension monitoring, the metacognitive process of evaluating and regulating comprehension. When comprehension breaks down due to an inconsistency either at the word-level (e.g., due to an unfamiliar word) or at the sentence-level (e.g., due to contradictory information), readers may identify the misunderstanding and take steps to regulate their comprehension. In the current study, we utilized two eye-movement tasks (one newly developed) to examine comprehension monitoring in third through fifth grade students (n = 123), when confronted with word- and sentence-level inconsistencies, by measuring the amount of time they read (gaze duration) and reread the target inconsistent words. We investigated how this skill may be associated with individual differences in age, reading comprehension ability, and vocabulary knowledge. The results showed that generally, all students detected the word-level inconsistencies, indicated by longer gaze durations, and attempted to regulate their comprehension after detecting both word- and sentence-level inconsistencies, as indicated by more time spent rereading. Students with stronger reading comprehension (when controlling for their vocabulary), and stronger vocabulary knowledge (when controlling for their reading comprehension) were more likely to attempt regulating their comprehension. In general, the difference between the control words and the inconsistent words was smaller for third graders and larger for fourth and fifth graders, which we argue indicates greater levels of comprehension monitoring - specifically employing repair strategies. With eye-tracking technology becoming more accessible, these tasks may be useful in assessing children's reading processes to better understand at which level of comprehension monitoring they may be struggling, which in return will allow us to develop more individualized instruction for all readers

On measuring the impact of hyperlinks on reading

We increasingly spend a vast amount of time on the Web and much of that time is spent reading. One of the main differences between reading non-Web based text and reading on the Web is the presence of hyperlinks within the text, linking various related Web content and Web pages together. Some researchers and commentators have claimed that hyperlinks hinder reading because they are a distraction that may have a negative effect on the reader’s ability to process the text. However, very few controlled experiments have been conducted to verify these claims.In the experiments documented here we utilise eye tracking as a new methodology for examining how we read hyperlinked text. An eye tracker was used to observe participant’s behaviour while reading. The results showed that hyperlinked text did not generally have a negative impact upon reading behaviour. However, participants did show a tendency to re-read sentences that contained hyperlinked uncommon (low frequency) words. This suggests that hyperlinks highlight important information to the reader and the hyperlinks add additional content which for more difficult concepts, invites rereading of the preceding text