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Introduction

This page contains the data & python scripts to reproduce the classification experiments reported in

@InProceedings{Abesser:2019:ICASSP,
  author =    {Jakob Abe{\ss}er and Meinard M{\"u}ller},
  title =     {Fundamental Frequency Contour Classification: A Comparison between Hand-Crafted and {CNN}-Based Features},
  booktitle = {Proceedings of the 44th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
  year =      {2019}
}

Python environment

  • In order to set-up the python environment, please install miniconda on your system, then run
conda env create -f conda_env.yml

Data preparation

  • Create a subfolder entitled data
  • Download the dataset from Zenodo and copy it into the data folder

Run experiments

  • Run the experiments using
python main.py
  • The results will be saved in the results folder