Estimation of dysperiodicities in disordered speech

This paper presents two methods for tracking vocal dysperiodicities in connected speech. The first is based on a long-term linear predictor with one coefficient and the second on a generalized variogram. Both analysis methods guarantee that a slight increase or decrease of irregularities in the speech signal produces a slight increase or decrease of the estimated vocal dysperiodicity trace. No spurious noise boosting occurs owing to erroneous insertions or omissions of speech cycles, or the comparison of speech cycles across phonetic boundaries. The two techniques differ with regard to how slow changes of speech cycle amplitudes are compensated for. They are compared on two speech corpora. One comprises stationary fragments of vowel [a] produced by 89 male and female normophonic and dysphonic speakers. Another comprises four French sentences as well as vowel [a] produced by 22 male and female normophonic and dysphonic speakers. Vocal dysperiodicities are summarized by means of global and segmental signal-to-dysperiodicity ratios. They are correlated with hoarseness scores obtained by means of perceptual ratings of the speech tokens. The two techniques obtain signal-to-dysperiodicity ratios that are statistically significantly correlated with the hoarseness scores. For connected speech, the segmental signal-to-dysperiodicity ratio correlates more strongly with perceptual scores of hoarseness than the global signal-to-dysperiodicity ratio.