This repository contains the analysis code for the Ghent Semi-spontaneous Speech Paradigm (GSSP). The GSSP is a picture description task that is used to capture (near) spontaneous speech in a controlled setting.

• The data is collected via a web application and can be found on kaggle
• The paradigm is described in detail in this preprint manuscript.
• The supplementals can be found here
• The notebooks README contains a thorough description of the speech parsing and analysis notebooks.

In a nutshell the r-scripts folder performs a thorough statistical analysis of the arousal & valence scores for the audio files. The outcome can be observed in a shiny html file. All speech data transformation and analysis is performed in the notebooks folder.

The utilized python packages are listed in the pyproject.toml file and the utilized R packages are listed in the scripts/r_packages.txt file.

├── docs │ └── cgn <-- CGN related documentation ├── GSSP_utils <-- Python functions shared across notebooks (and CGN parsing) ├── loc_data <-- Local data shared across notebooks ├── notebooks <-- the analysis Jupyter notebooks ├── reports <-- Generated figures from the notebooks └── scripts <-- R scripts for statistical analysis & shiny app

• A preprint manuscript is available on psyArxiv.

@misc{van_der_donckt_2023, title={Ecologically Valid Speech Collection in Behavioral Research: The Ghent Semi-spontaneous Speech Paradigm (GSSP)}, url={psyarxiv.com/e2qxw}, DOI={10.31234/osf.io/e2qxw}, publisher={PsyArXiv}, author={Van Der Donckt, Jonas and Kappen, Mitchel and Degraeve, Vic and Demuynck, Kris and Vanderhasselt, Marie Anne and Van Hoecke, Sofie}, year={2023}, month={Mar} }

👤 Jonas Van Der Donckt, Mitchel Kappen