Optimization of Glottal Onset Peak Detection Algorithm for Accurate Jitter Measurement

Jitter is an acoustic parameter used as input for intelligent systems for the diagnosis of speech related pathologies. This work has the objective to improve an algorithm that allows to extract vocal parameters, and thus improve the accuracy measurement of absolute jitter parameter. Some signals were analyzed, where signal to signal was compared in order to try to understand why the values are different in some signal between the original algorithm and the reference software. In this way, some problems were found that allowed to adjust the algorithm, and improve the measurement accuracy for those signals. Subsequently, a comparative analysis was performed between the values of the original algorithm, the adjusted algorithm and the Praat software (assumed as reference). By comparing the results, it was concluded that the adjusted algorithm allows the extraction of the absolute jitter with values closer to the reference values for several speech signals. For the analysis, sustained vowels of control and pathological subjects were used.