lexsync: Lexical optimisation and hardware-timed experiment generation

Package Web application Open Materials
Bernabeu, P. (2026) — Version 0.1.0 on the Comprehensive R Archive Network (CRAN) and Version 0.1.1 on PyPI [Computer software] software
Code DOI R documentation Python documentation R app guide Python app guide CRAN PyPI Blog post

Abstract

Twin R and Python packages for selecting and matching lexical stimuli, counterbalancing lists, generating pseudowords, and writing PsychoPy, OpenSesame and jsPsych experiments, the first two with hardware-timed electroencephalography (EEG) triggers.

Overview

lexsync (Bernabeu, 2026a, 2026b) turns a lexical design into a checked set of stimuli and experiment files. It separates the candidate corpus from the design specification, reports whether matching and counterbalancing succeeded, and carries the resulting item table into PsychoPy, OpenSesame or jsPsych. The shared R/Python format makes the design inspectable before any presentation software is involved.

The repository also carries two browser front-ends over the same engines, a Shiny app for R and a Streamlit app for Python. Each assembles a design through the interface, runs the same pipeline as the packages and exports the code that reproduces it. Launch either one from the repository root, so that it finds the bundled corpora and the example item tables.

The main quality-control question for a set of lexical materials is whether the conditions remain comparable on the control variables chosen by the researcher. lexsync answers it as a claim of equivalence, testing each control against a bound fixed before selection, so a control passes only when its interval stays inside that bound. Figure 1 reports that test for the example design.

Dot-and-whisker plot of standardised differences, high minus low frequency, with 90% confidence intervals for word length, neighbourhood density and OLD20. All three estimates lie near zero and all three intervals fall inside the shaded equivalence region from minus 0.5 to plus 0.5
Realised Balance Between the Frequency Conditions on Each Control Variable, With 90% Confidence Intervals Against the Prespecified Equivalence Region. Shading marks the equivalence region set by the schema's default bound, from minus to plus half a standard deviation.

Reproducible Hand-Off

Save the design, the source lexicon, the matching report and the generated experiment together. Before any electroencephalography (EEG) recording, verify the exported timing, trigger codes, trial order and counterbalancing in the target presentation framework. The R documentation, Python documentation and companion blog post provide the complete workflow.

References

Bernabeu, P. (2026a). lexsync: Lexical optimisation and hardware-timed experiment generation (Version 0.1.0) [Computer software]. Comprehensive R Archive Network (CRAN). https://doi.org/10.32614/CRAN.package.lexsync

Bernabeu, P. (2026b). lexsync: Lexical optimisation and hardware-timed experiment generation (Version 0.1.1) [Computer software]. PyPI. https://pypi.org/project/lexsync/0.1.1/

Documentation

R documentation Python documentation
software R Python psycholinguistics experimental stimuli EEG

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