Fitting synthetic to clinical kymographic images for deriving kinematic vocal fold parameters: Application to left-right vibratory phase differences

Abstract In this paper we present the extraction of kinematic vocal fold parameters from videokymographic images and the visual estimation of phase differences between the left and right vocal folds. We used a model of vocal fold vibrations with kinematic parameters to generate synthetic kymograms. To extract kinematic model parameters from the images, we propose a fitting procedure for error minimization. We used the “Structural Dissimilarity Index Measure” (DSSIM) and the “Cross Uncorrelation” (CUC) as error measures. The minimization procedure was used to evaluate 55 clinical kymograms and two sets of 50 synthetic kymograms each. The two sets of synthetic kymograms were generated using the probability density functions (PDFs) of the model parameters, which were obtained by fitting the clinical kymograms using the two error measures. The relative parameter estimation errors range up to 15% for the most important parameters, indicating acceptable performance of the fitting procedure. Additionally, the phase difference was assessed by three observers with integer ratings ranging from 0 (negligible) to 3 (large phase difference). The Fleiss’ Kappa of 0.46 and its standard error 0.03 indicated a moderate agreement among the three observers. ROC analysis was carried out for estimating thresholds for predicting the ratings. Moderate to good prediction accuracies (0.69–0.91) for the clinical corpus and very good prediction accuracy (0.92–1.00) for the synthetic corpora were observed.