Title :
A new algorithm for instantaneous F0 speech extraction based on Ensemble Empirical Mode Decomposition
Author :
Schlotthauer, Gaston ; Torres, Maria Eugenia ; Rufiner, Hugo L.
Author_Institution :
Lab. de Senales y Dinamicas no Lineales, Univ. Nac. de Entre Rios, Parana, Argentina
Abstract :
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 data-driven 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.
Keywords :
feature extraction; speech recognition; AM-FM component sum; data driven method; ensemble empirical mode decomposition; instantaneous fundamental frequency speech extraction; intrinsic mode functions; normal vowel sound; pathological sustained vowel; pathological voice processing; signal decomposition; speech fundamental frequency; Abstracts; Correlation; Indexes; Transforms; Visualization;
Conference_Titel :
Signal Processing Conference, 2009 17th European
Conference_Location :
Glasgow
Print_ISBN :
978-161-7388-76-7