Cuentos: A Large-Scale Eye-Tracking Reading Corpus on Spanish Narrative Texts.

Area of Science:

• Cognitive Science
• Linguistics
• Computational Neuroscience

Background:

• Eye-tracking is vital for understanding reading and cognitive processes.
• Limited empirical data exists for Spanish reading behavior.
• Cross-linguistic differences in reading are not well-understood.

Purpose of the Study:

• To present the largest publicly available Spanish eye-tracking dataset.
• To facilitate research on Spanish reading patterns and cognitive processes.
• To enable development of computational models for reading and NLP.

Main Methods:

• Collected eye-tracking data from 113 native Spanish speakers reading short and long stories.
• Dataset includes over 940,000 fixations across approximately 40,000 words.
• Data covers natural reading scenarios with varying story lengths and reading repetitions.

Main Results:

• Established the largest Spanish eye-tracking dataset to date.
• Captured extensive data on natural reading behavior in Spanish.
• Provided a rich resource for diverse research applications.

Conclusions:

• The dataset is a significant contribution to Spanish reading research.
• It enables investigation of language-specific reading phenomena.
• Facilitates advancements in computational linguistics and reading research.