Data-canvas application for speech perception and production data

Data visualization in speech communication research often requires specialized coding skills, which can limit accessibility for students, clinicians, and researchers unfamiliar with programming. This project aimed to develop an intuitive and flexible data visualization application, DataCanvas, which allows users to explore, analyze, and visualize behavioral speech perception and production datasets without requiring coding expertise. The application was built using the Shiny framework in R and offers an interactive interface that allows users to upload datasets, choose from multiple visualization options (e.g., scatterplots, boxplots), and customize plots. This presentation will demonstrate the use of DataCanvas for a study involving speech perception and production data collected from adult cochlear implant recipients. Boxplots and scatterplots were created in DataCanvas to visualize trends in accuracy, reaction times, and sensitivity, and to explore relationships among factors. DataCanvas simplifies the data visualization process for speech communication researchers by removing coding-related obstacles and providing a highly adaptable tool for data exploration and presentation. Future development will focus on expanding the app's functionality and customization options based on feedback from researchers, students, and clinicians. Areas of suggested improvements include better data integration, statistical analyses, acoustic analyses, and more data visualization functionality.