Presenting the Signers’ Eye-movements in English Reading (SEER) Corpus: An eye-tracking dataset of reading behaviors by deaf early signers and hearing non-signers

Eye-tracking corpora have advanced our understanding of reading processes by providing large-scale datasets of naturalistic reading behavior. However, existing corpora have almost exclusively sampled from typically hearing readers of spoken languages. Here, we present the Signers' Eye-movements in English Reading (SEER) Corpus, a dataset of eye-movement behaviors from 41 skilled deaf adult readers who are early signers of American Sign Language (ASL), as well as a comparative group of 101 typically hearing monolingual English readers. Participants read 200 English sentences presented one at a time. In addition to eye-tracking data, the corpus includes detailed participant information: a standardized measure of reading proficiency, spelling recognition, and nonverbal intelligence for all participants. Information for the deaf participants include ASL comprehension scores, age of ASL acquisition, and phonological awareness scores (for a subset of participants). We report comparative analyses of reading behaviors at both the word level and sentence level. We also examine group differences in the effects of word length, frequency, and surprisal on local measures. The results indicate stronger effects of length and surprisal, but equivalent frequency effects (on content words) for deaf compared to hearing readers. The SEER Corpus offers researchers the opportunity to test hypotheses about reading development and efficiency in bimodal bilinguals who are first language users of ASL and skilled readers of English, supporting broader investigations of visual language processing. The corpus is preregistered and publicly available ( https://doi.org/10.17605/OSF.IO/7P4F2 ) to facilitate replication, cross-study comparisons, and exploration of preliminary hypotheses in this understudied population.