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

TL;DR

Hylog is a new hybrid logging system that captures detailed on-screen text transformations in non-alphabetic scripts, enabling more comprehensive analysis of IME-mediated typing processes.

Contribution

It introduces a modular, open-source hybrid logging system combining keylogging and ecological text logging for detailed analysis of non-alphabetic script text production.

Findings

Successfully captured keypresses and text transformations in Chinese IME

Enabled analysis of cognitive restrictions at different linguistic layers

Demonstrated system's feasibility with a proof-of-concept study

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.