TypeShift: A User Interface for Visualizing the Typing Production Process
This tool addresses the need for researchers to analyze noisy typing data, but it is incremental as it adapts existing visualization methods to a specific domain.
The researchers tackled the problem of visualizing complex linguistic patterns in typing production by developing TypeShift, a tool that enables comparison of specific linguistic phenomena and individual sessions against group averages, with a web demo and source code provided.
TypeShift is a tool for visualizing linguistic patterns in the timing of typing production. Language production is a complex process which draws on linguistic, cognitive and motor skills. By visualizing holistic trends in the typing process, TypeShift aims to elucidate the often noisy information signals that are used to represent typing patterns, both at the word-level and character-level. It accomplishes this by enabling a researcher to compare and contrast specific linguistic phenomena, and compare an individual typing session to multiple group averages. Finally, although TypeShift was originally designed for typing data, it can easy be adapted to accommodate speech data, as well. A web demo is available at https://angoodkind.shinyapps.io/TypeShift/. The source code can be accessed at https://github.com/angoodkind/TypeShift.