American Journal of Applied Sciences

An Improved Time Domain Pitch Detection Algorithm for Pathological Voice

Mohd Redzuan Jamaludin, Sheikh Hussain Shaikh Salleh, Tan Tian Swee, Kartini Ahmad, Ahmad Kamarul Ariff Ibrahim and Kamarulafizam Ismail

DOI : 10.3844/ajassp.2012.93.102

American Journal of Applied Sciences

Volume 9, Issue 1

Pages 93-102

Abstract

Problem statement: The present study proposes a new pitch detection algorithm which could potentially be used to detect pitch for disordered or pathological voices. One of the parameters required for dysphonia diagnosis is pitch and this prompted the development of a new and reliable pitch detection algorithm capable of accurately detect pitch in disordered voices. Approach: The proposed method applies a technique where the frame size of the half wave rectified autocorrelation is adjusted to a smaller frame after two potential pitch candidates are identified within the preliminary frame. Results: The method is compared to PRAAT’s standard autocorrelation and the result shows a significant improvement in detecting pitch for pathological voices. Conclusion: The proposed method is more reliable way to detect pitch, either in low or high pitched voice without adjusting the window size, fixing the pitch candidate search range and predefining threshold like most of the standard autocorrelation do.

Copyright

© 2012 Mohd Redzuan Jamaludin, Sheikh Hussain Shaikh Salleh, Tan Tian Swee, Kartini Ahmad, Ahmad Kamarul Ariff Ibrahim and Kamarulafizam Ismail. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.