## 5 Architecture of the Proposed System
### Feature Extraction
Non-linear source-filter coupling clearly indicates sound source instabilities, which are one of the symptoms of PD. The goal of this study is to detect manifestations of a source-filter non-linearity interaction appearing in the form of chaotic vocal fold vibrations. This is what the non-linearity phonation process means. Figure 2 shows the voice waveforms of the sustained phonation of the vowel 'a' and the contour of the fundamental frequency. To achieve greater stability of this descriptor, we decided to calculate the fundamental frequency using two methods: the autocorrelation method and the cepstral method. From Figure 2, phonation analysis shows that the contour of healthy people is more stable than the contour obtained from PD patients. People with PD have lower vocal fold strength. This demonstrates the irregular work of the vocal folds and, more precisely, the irregular frequency of their opening and closing. As a result, impaired laryngeal operation is the case for people with [PERSON]'s disease. This is particularly visible in the second half of the analyzed time period. People with PD have difficulty maintaining the utterance of a sound with the same pitch. This is caused by occasional loss of phonation in people with PD (whisper). The following descriptors were used to evaluate the variability of the phonation process:  
* Jitter group parameters (Jitter [%], Jitta [\(\mu\)s], RAP [%], PPQ5 [%]);
* Shimmer group parameters (shimmer [%], APQ3 [%], APQ5 [%], APQ11 [%];
* PVI (pathology vibrato index). Jitter, shimmer, and \(F_{0}\) parameters are directly associated with vocal fold vibration. These are the parameters most frequently used in voice apparatus analysis [81]. All healthy voices exhibit natural fundamental tone frequency variability characterized by a smooth vibrato and micro-vibrations, which are detected, e.g., using traditional jitter measures. These parameters can be analyzed under a steady voice producing a vowel continuously. Jitter parameters are defined as a change in the basal frequency of the laryngeal tone. Jitter represents the average absolute difference between two consecutive periods of speech signal and is commonly referred to as Jitta. Local jitter is used to represent the average absolute difference between two consecutive periods divided by the mean period. Another parameter in this group is RAP, which represents the mean absolute difference of a given period and the average of a period with its two neighbors divided by the mean period. PPQn (pitch period perturbation quotient) parameters were also defined, defining the relative assessment of short- or long-term changes in the fundamental frequency within the analyzed voice sample, with a user-defined smoothing coefficient. The jitter is affected mainly by the lack of control over the vibration of the cords. The voices of patients with pathologies often have a higher percentage of jitter [81]. Shimmer parameters are defined as changes in the amplitude of a sound wave (speech signal) in successive cycles of vocal folds. A parameter called shimmer represents the mean absolute difference between the amplitudes of two consecutive periods divided by the mean amplitude. The parameters from the APQn group represent the quotient of amplitude disturbances over n periods, i.e., the mean absolute difference between the amplitude of the period and the mean amplitude of its (n \(-1\)) neighbors divided by the mean amplitude. The higher the values, the greater the instability of the voice amplitude in the analyzed signals [82]. A representation of jitter and shimmer perturbation measures in speech signals is shown in Figure 3.  
Another parameter is the PVI (pathology vibrato index). Vibrato means a rapid and regular fluctuation of the fundamental frequency of the laryngeal tone \(F_{0}\), which occurs during prolonged vowel phonation.