A New Algorithm for Instantaneous F0 Speech Extraction Based on Ensemble Empirical Mode Decomposition

GASTÓN SCHLOTTHAUER; MARÍA EUGENIA TORRES; HUGO LEONARDO RUFINER

Glasgow, Escocia

Conferencia; 17th European Signal Processing Conference EUSIPCO 09; 2009

European Association for Signal, Speech, and Image Processing (EURASIP, www.eurasip.org)

In this work, a new instantaneous fundamental frequency extraction method is presented, with the attention especially focused on its robustness for pathological voices processing. It is based on the Ensemble Empirical Mode Decomposition (EEMD) algorithm, which is a completely datadriven method for signal decomposition into a sum of AM - FM components, called Intrinsic Mode Functions (IMFs) or modes. Our results show that the speech fundamental frequency can be captured in a single IMF. We also propose an algorithm for selecting the mode where the fundamental frequency can be found, based on the logarithm of the power of the IMFs. The instantaneous frequency is then extracted by means of well-known techniques. The behaviour of the proposed method is compared with other two ones (Robust Algorithm for Pitch Tracking -RAPT- and auto-correlation based algorithms), both in normal and pathological sustained vowels.