articleIEEE Transactions on Biomedical EngineeringJan 9, 2012GREEN OA

Novel Speech Signal Processing Algorithms for High-Accuracy Classification of Parkinson's Disease

Science Oxford · University of Oxford · +3 more institutions

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Abstract

There has been considerable recent research into the connection between Parkinson's disease (PD) and speech impairment. Recently, a wide range of speech signal processing algorithms (dysphonia measures) aiming to predict PD symptom severity using speech signals have been introduced. In this paper, we test how accurately these novel algorithms can be used to discriminate PD subjects from healthy controls. In total, we compute 132 dysphonia measures from sustained vowels. Then, we select four parsimonious subsets of these dysphonia measures using four feature selection algorithms, and map these feature subsets to a binary classification response using two statistical classifiers: random forests and support…

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718
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FWCI
15.53
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100%
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Authors

5

Topics & keywords

Keywords
  • Statistical classification
  • Feature selection
  • Random forest
  • Binary classification
  • Feature (linguistics)
  • Support vector machine
  • Speech processing
  • Computer science
UN Sustainable Development Goals
  • Reduced inequalities
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