The presentation concerns a method that obtains the size and frequency of vocal tremor in speech sounds sustained by normal speakers and patients suffering from neurological disorders. The glottal cycle lengths are tracked in the temporal domain via salience analysis and dynamic programming. The cycle length time series is then decomposed into a sum of oscillating components by empirical mode decomposition the instantaneous envelopes and frequencies of which are obtained via an AM-FM decomposition. Based on their average instantaneous frequencies, the empirical modes are then assigned to four categories (intonation, physiological tremor, neurological tremor as well as jitter) and added within each. The within-category size of the cycle length perturbations is estimated via the standard deviation of the empirical mode sum divided by the average cycle length. The tremor frequency within the neurological tremor category is obtained via a weighted instantaneous average of the mode frequencies followed by a weighted temporal average. The method is applied to two corpora of vowels sustained by 123 and 74 control and 456 and 205 Parkinson speakers respectively.
Bibliographic reference. Mertens, Christophe / Grenez, Francis / Viallet, François / Ghio, Alain / Skodda, Sabine / Schoentgen, Jean (2015): "Vocal tremor analysis via AM-FM decomposition of empirical modes of the glottal cycle length time series", In INTERSPEECH-2015, 766-770.