Formant Estimation and Tracking using Probabilistic Heat-Maps

Yosi Shrem ([email protected]),
Felix Kreuk,
Joseph Keshet ([email protected]).

FormantsTracker is a software package for Formant Tracking and Estiamtion using deep learning.

We propose a new modeling for measuring the formants' frequencies using probabilistic heat-maps rather than traditional regression. This technique allows for flexibility in the predictions to support both in-distribution and out-of-distribution (OOD) samples with greater precision.

The paper was present at Interspeech 2022 - Formant Estimation and Tracking using Probabilistic Heat-Maps. If you find our work useful please cite :

@article{shrem2022formant,
  title={Formant Estimation and Tracking using Probabilistic Heat-Maps},
  author={Shrem, Yosi and Kreuk, Felix and Keshet, Joseph},
  journal={arXiv preprint arXiv:2206.11632},
  year={2022}
}

Installation instructions:

1. First, create a conda virtual environment and activate it:

conda create -n FormantsTracker python=3.9 -y
conda activate FormantsTracker

2. Then, clone this repository and install dependencies with:

git clone https://github.com/MLSpeech/FormantsTracker.git
cd FormantsTracker
pip install -r requirements.txt

How to use:

You can either set the paths for the run (opt1) or use the default values (opt2). The generated predictions are for every 10ms frame.

Option 1 :

• Provide the path for test_dir and predictions_dir as arguments. For example:

  python main.py test_dir=<data_dir_path> predictions_dir=<predictions_dir_path>
  

• Note: You can also change the default values at ./conf/config.yaml.

Option 2 :

• Place your .wav files in the ./test_dir/ directory.
• Then, run :

  python main.py
  

• The predictions will be at ./predictions directory.
• Note: You can also place directories that contain the .wav files, there is no need to re-arrange your data. For example:

    ./data
          └───dir1
          │   │   1.wav
          │   │   2.wav
          │   │   3.wav
          │               │   
          └───dir2
              │   1.wav
              │   2.wav
              │   3.wav