title: PyParse: a semiautomated system for scoring spoken recall data.
abstract: 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.
authors.affiliation: Princeton University, Princeton, New Jersey, USA.
authors.forename: Alec
authors.initials: A
authors.lastname: Solway
authors.forename: Aaron S
authors.initials: AS
authors.lastname: Geller
authors.forename: Per B
authors.initials: PB
authors.lastname: Sederberg
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Kahana
mesh_terms: D003627:Data Interpretation, Statistical; D006801:Humans; D008570:Memory, Short-Term; D011381:Programming Languages; D021641:Recognition, Psychology; D014825:Vocabulary