Hylog: A Hybrid Approach to Logging Text Production in Non-alphabetic Scripts

Abstract:Research keyloggers are essential for cognitive studies of text production, yet most fail to capture the on-screen transformations performed by Input Method Editors (IMEs) for non-alphabetic scripts. To address this methodological gap, we present Hylog, a novel hybrid logging system that combines analytical keylogging with ecological text logging for a more complete and finer-grained analysis. Our modular, open-source system uses plug-ins for standard applications (Microsoft Word, Google Chrome) to capture both keyboard output and rendered text, which a hybridizer module then synchronizes into a dual trace. To validate the system's technical feasibility and demonstrate its analytical capabilities, we conducted a proof-of-concept study where two volunteers translated a text into simplified Chinese. Hylog successfully captured keypresses and temporal intervals between Latin letters, Chinese characters, and IME confirmations -- some measurements invisible to traditional keyloggers. The resulting data enable the formulation of new, testable hypotheses about the cognitive restrictions and affordances at different linguistic layers in IME-mediated typing. Our plug-in architecture enables extension to other IME systems and fosters more inclusive multilingual text-production research.

Computation and Language (cs.CL)

arXiv:2601.17753 [cs.CL]

(or arXiv:2601.17753v2 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2601.17753 Focus to learn more arXiv-issued DOI via DataCite

https://doi.org/10.1109/ACCESS.2026.3718565 Focus to learn more DOI(s) linking to related resources

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