Comparison of Telephone Recordings and Professional Microphone Recordings for Early Detection of Parkinson’s Disease, Using Mel-Frequency Cepstral Coefficients with Gaussian Mixture Models

Laetitia Jeancolas, Graziella Mangone, Jean-Christophe Corvol, Marie Vidailhet, Stéphane Lehéricy, Badr-Eddine Benkelfat, Habib Benali, Dijana Petrovska-Delacrétaz


Vocal impairments are among the earliest symptoms in Parkinson’s Disease (PD). We adapted a method classically used in speech and speaker recognition, based on Mel-Frequency Cepstral Coefficients (MFCC) extraction and Gaussian Mixture Model (GMM) to detect recently diagnosed and pharmacologically treated PD patients. We classified early PD subjects from controls with an accuracy of 83%, using recordings obtained with a professional microphone. More interestingly, we were able to classify PD from controls with an accuracy of 75% based on telephone recordings. As far as we know, this is the first time that audio recordings from telephone network have been used for early PD detection. This is a promising result for a potential future telediagnosis of Parkinson’s disease.


 DOI: 10.21437/Interspeech.2019-2825

Cite as: Jeancolas, L., Mangone, G., Corvol, J., Vidailhet, M., Lehéricy, S., Benkelfat, B., Benali, H., Petrovska-Delacrétaz, D. (2019) Comparison of Telephone Recordings and Professional Microphone Recordings for Early Detection of Parkinson’s Disease, Using Mel-Frequency Cepstral Coefficients with Gaussian Mixture Models. Proc. Interspeech 2019, 3033-3037, DOI: 10.21437/Interspeech.2019-2825.


@inproceedings{Jeancolas2019,
  author={Laetitia Jeancolas and Graziella Mangone and Jean-Christophe Corvol and Marie Vidailhet and Stéphane Lehéricy and Badr-Eddine Benkelfat and Habib Benali and Dijana Petrovska-Delacrétaz},
  title={{Comparison of Telephone Recordings and Professional Microphone Recordings for Early Detection of Parkinson’s Disease, Using Mel-Frequency Cepstral Coefficients with Gaussian Mixture Models}},
  year=2019,
  booktitle={Proc. Interspeech 2019},
  pages={3033--3037},
  doi={10.21437/Interspeech.2019-2825},
  url={http://dx.doi.org/10.21437/Interspeech.2019-2825}
}