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Voice fundamental frequency extraction algorithm based on ensemble empirical mode decomposition and entropies.
| Content Provider | CiteSeerX |
|---|---|
| Author | Schlotthauer, G. Torres, M. E. Rufiner, H. L. |
| Abstract | Abstract — A new algorithm for pitch extraction based on the Ensemble Empirical Mode Decomposition (EEMD) is presented. Applications to normal and pathological voices are considered. EEMD is a completely data-driven method for signal decomposition into a sum of AM- FM components, called Intrinsic Mode Functions (IMFs) or modes, which can be written as A()cos ( t ϕ ()) t. The voice fundamental frequency (F0) can be captured in a single IMF, allowing its extraction by means of well known AM-FM separating techniques. An entropy based selection algorithm is here proposed, in order to determine the mode that holds the fundamental frequency. The behavior of the proposed method is compared with other two ones, both in normal and pathological sustained vowels. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Ensemble Empirical Mode Decomposition Voice Fundamental Frequency Extraction Algorithm Pitch Extraction Single Imf Data-driven Method Voice Fundamental Frequency Intrinsic Mode Function New Algorithm Signal Decomposition Selection Algorithm Fm Component Pathological Voice Fundamental Frequency |
| Content Type | Text |
