Computational Diagnosis of Parkinson's Disease Directly from Natural Speech Using Machine Learning Techniques

@article{Frid2014ComputationalDO,
  title={Computational Diagnosis of Parkinson's Disease Directly from Natural Speech Using Machine Learning Techniques},
  author={A. Frid and Hananel Hazan and D. Hilu and L. Manevitz and L. Ramig and S. Sapir},
  journal={2014 IEEE International Conference on Software Science, Technology and Engineering},
  year={2014},
  pages={50-53}
}
  • A. Frid, Hananel Hazan, +3 authors S. Sapir
  • Published 2014
  • Computer Science
  • 2014 IEEE International Conference on Software Science, Technology and Engineering
The human voice signal carries much information in addition to direct linguistic semantic information. This information can be perceived by computational systems. In this work, we show that early diagnosis of Parkinson's disease is possible solely from the voice signal. This is in contrast to earlier work in which we showed that this can be done using hand-calculated features of the speech (such as formants) as annotated by professional speech therapists. In this paper, we review that work and… Expand
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