Eye-tracking during natural reading of stories in Spanish

Eye-tracking is a well-established methodology to study reading processes. Our gaze jumps from word to word, sampling information from text almost sequentially. The time spent on each word, along with patterns of skipping or revisiting, provides proxies for different cognitive processes during comprehension. However, few studies have focused on Spanish, where empirical data remain scarce, and little is known about how findings from other languages translate to Spanish reading behavior. We present the largest publicly available Spanish eye-tracking dataset to date, comprising readings of self-contained stories from 113 native speakers (mean age 23.8; 61 females, 52 males). The dataset includes both long stories (3300 ± 747 words, 11 participants per item on average) and short stories (795 ± 135 words, 50 participants per item on average), providing extensive coverage of natural reading scenarios. This comprehensive resource offers valuable opportunities to investigate eye movement patterns during Spanish reading, explore language-specific cognitive processes, examine Spanish linguistic phenomena, and develop computational algorithms for reading research and natural language processing applications.If you use this dataset, please provide the appropriate citation:<br>Travi, F., Bianchi, B., Slezak, D.F. <i>et al.</i> Cuentos: A Large-Scale Eye-Tracking Reading Corpus on Spanish Narrative Texts. <i>Sci Data</i> (2026). https://doi.org/10.1038/s41597-026-06798-z<br>To view and analyse the data, we recommend using the following: https://github.com/NeuroLIAA/reading-etParticipants' age and gender information are not publicly available. However, they can be made available for research purposes. If needed, contact us specifying its purpose.