Analysis of Voice for Parkinson’s Disease Persons Using Dynamic Time Warping Technique

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 308)

Abstract

This paper presents a dynamic time warping (DTW) technique-based analysis of voice for distinguishing Parkinson’s disease (PD) persons from healthy persons. Mel frequency cepstral coefficient (MFCC) algorithm with MATLAB coding has been used to process voice samples. MFCC is converted into vector using MATLAB. DTW is useful for matching of voice samples. DTW-based matching percentage between PD-affected persons is 80.2163 %, whereas it is 72.2588 % between healthy persons. First coefficient of MFCC shows large values in case of PD-affected persons.

Keywords

Analysis MFCC Dynamic time warping Parkinson’s disease Matching Voice 

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Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.School of VLSI Design and Embedded SystemsNIT KurukshetraKurukshetraIndia

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