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PyParse: a semiautomated system for scoring spoken recall data
Alec Solway1, Aaron S Geller, Per B Sederberg
1Princeton University, Princeton, New Jersey, USA.
None:
Studies of human memory often generate data on the sequence and timing of recalled items, but scoring such data using conventional methods is difficult or impossible. We describe a Python-based semiautomated system that greatly simplifies this task. This software, called PyParse, can easily be used in conjunction with many common experiment authoring systems. Scored data is output in a simple ASCII format and can be accessed with the programming language of choice, allowing for the identification of features such as correct responses, prior-list intrusions, extra-list intrusions, and repetitions.
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