Research Article Open Access

An Improved Time Domain Pitch Detection Algorithm for Pathological Voice

Mohd Redzuan Jamaludin1, Sheikh Hussain Shaikh Salleh1, Tan Tian Swee1, Kartini Ahmad1, Ahmad Kamarul Ariff Ibrahim1 and Kamarulafizam Ismail1
  • 1 Centre for Biomedical Engineering, University Technology Malaysia Skudai, Malaysia


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.

American Journal of Applied Sciences
Volume 9 No. 1, 2012, 93-102


Submitted On: 10 December 2010 Published On: 21 November 2011

How to Cite: Jamaludin, M. R., Salleh, S. H. S., Swee, T. T., Ahmad, K., Ibrahim, A. K. A. & Ismail, K. (2012). An Improved Time Domain Pitch Detection Algorithm for Pathological Voice. American Journal of Applied Sciences, 9(1), 93-102.

  • 12 Citations



  • Pitch Detection Algorithm (PDA)
  • dysphonia
  • autocorrelation
  • Merged Normalized Forward Backward Correlation (MNFBC)
  • pathological voices
  • Hilbert-Huang Transform (HHT)
  • time domain
  • mean error
  • Auto Correlation Function (ACF)