Empirical mode decomposition (EMD) algorithm is proposed as an alternative to decompose the log of the magnitude spectrum of the speech signal into its harmonic, envelope and noise components and the harmonic-to-noise ratio is used to summarize the degree of disturbance in the speech signal. The empirical mode decomposition algorithm is a tool for the analysis of multi-component signals. The analysis method does not require a priori fixed basis function like conventional analysis methods (e.g. Fourier transform and wavelet transform).The proposed method is tested on synthetic vowels and natural speech. The corpus of synthetic vowels comprises 48 stimuli of synthetic sounds [a] that combine three values of vocal frequency, four levels of jitter frequency and four levels of additive noise. The corpora of natural speech comprise a concatenation of the vowel [a] with two Dutch sentences produced by 28 normophonic and 223 speakers with different degrees of dysphonia.
Index Terms: Disordered voices, empirical mode decomposition, harmonic-to-noise ratio.
Bibliographic reference. Kacha, Abdellah / Grenez, Francis / Schoentgen, Jean (2012): "Assessment of disordered voices using empirical mode decomposition in the log-spectral domain", In INTERSPEECH-2012, 66-69.