This repository is for supplementary codes used to explore and analyze the K-EmoPhone Dataset.
- Description of the dataset: TBD
- Dataset URL: https://doi.org/10.5281/zenodo.7606611
We have run this code under the environment as below:
- OS: Ubuntu 20.04 installed with Windows Subsystem for Linux (WSL)
- This code highly depends on a python multiprocessing library, ray which does not fully support Windows OS.
- CPU: AMD Ryzen 9 5900x 12-Core
- This is not mandatory; you can run this code (with a minor modification) although you have the smaller number of cores.
- RAM: 128GB
- This is not mandatory; we expected about 40GB of RAM to be required (but not tested).
In addition, you need to install conda for managing packages and virtual environment.
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Download the K-EmoPhone dataset.
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Download this repository
$ git clone https://github.com/Kaist-ICLab/K-EmoPhone_SupplementaryCodes.git
$ cd K-EmoPhone_SupplementaryCodes-
Replicate our conda environment (environment.yml), referring to this.
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Run your own Jupyter environment.
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Then, open analysis.ipynb.