Vocal Dynamic Visual Pattern for voice characterization
María Eugenia Dájer, F A S Andrade, Arlindo Neto Montagnoli, J.C. Pereira, Domingos Hiroshi Tsuji · Journal of Physics Conference Series · 2011
Voice assessment requires simple and painless exams. Modern technologies provide the necessary resources for voice signal processing. Techniques based on nonlinear dynamics seem to asses the complexity of voice more accurately than other methods. Vocal dynamic visual pattern (VDVP) is based on nonlinear methods and provides qualitative and quantitative information. Here we characterize healthy and Reinke's edema voices by means of perturbation measures and VDVP analysis. VDPD and jitter show different results for both groups, while amplitude perturbation has no difference. We suggest that VDPD analysis improve and complement the evaluation methods available for clinicians.