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