Mathematical morphology preprocessing to mitigate AWGN effects: improving pitch tracking performance in hard noise conditions

  • Authors:

  • Pere Martí-Puig;Jordi Solé-Casals;Ramon Reig-Bolaño;Vladimir Zaiats

  • Affiliations:

  • Digital Technologies Group, University of Vic, Vic, Spain;Digital Technologies Group, University of Vic, Vic, Spain;Digital Technologies Group, University of Vic, Vic, Spain;Digital Technologies Group, University of Vic, Vic, Spain

  • Venue:
  • NOLISP'09 Proceedings of the 2009 international conference on Advances in Nonlinear Speech Processing
  • Year:
  • 2009

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Abstract

In this paper we show how a nonlinear preprocessing of speech signal -with high noise- based on morphological filters improves the performance of robust algorithms for pitch tracking (RAPT). This result happens for a very simple morphological filter. More sophisticated ones could even improve such results. Mathematical morphology is widely used in image processing in where it has found a great amount of applications. Almost all its formulations derived in the two-dimensional framework are easily reformulated to be adapted to one-dimensional context.