title: Quantitative assessment of the use of continuous wavelet transform in the analysis of the fundamental frequency disturbance of the synthetic voice.
abstract: The aim of this work is to investigate quantitatively the capability of the Continuous Wavelet Transform (CWT) as a tool to estimate (calculate) Jitter and Shimmer, assessing the error between these indices calculated in each Wavelet decomposition and the ones for the original signal, for several dilatation levels. Two synthetic vowels /a/ were generated with the fundamental frequencies of 120 Hz for male and 220 Hz for female, by an autoregressive 22 coefficient all-pole model, and Jitter and Shimmer were introduced to the signal using five different percentage variations. The signals were decomposed by CWT in eight levels of dilatation (1, 2, 4, 8, 16, 32, 64 and 128), using the Mexican Hat, Meyer and Morlet real bases. Jitter and Shimmer were calculated for the original signals and all eight levels of decompositions and then the errors between the indices in the decompositions and the original signals were calculated. It can be concluded that CWT can be used as a tool for pre-processing the signal to measure Shimmer preferentially, and Jitter, instead of using the original signal to do that. The Mexican Hat base provided the lowest errors for Shimmer analysis, where the best dilatation level was 8 (error below 0.1%). In addition, the errors associated with Shimmer index, in general, are lower than the ones associated with Jitter index.
authors.affiliation: CPGEE-DELET-UFRGS, Universidade Federal do Rio Grande do Sul, Escola de Engenharia Elétrica, Av. Osvaldo Aranha, 103-sala 206-B, Porto Alegre, RS, Brazil. aparraga@iee.ufrgs.be
authors.forename: Adriane
authors.initials: A
authors.lastname: Parraga
authors.forename: Milton A
authors.initials: MA
authors.lastname: Zaro
authors.forename: Adalberto
authors.initials: A
authors.lastname: Schuck
mesh_terms: D000465:Algorithms; D005260:Female; D006801:Humans; D008297:Male; D008954:Models, Biological; D009622:Noise; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013060:Speech / Q000145:classification*; D013064:Speech Disorders / Q000145:classification* / Q000503:physiopathology*; D013068:Speech Production Measurement / Q000379:methods*; D013071:Speech, Alaryngeal