## 5 Architecture of the Proposed System
### Feature Extraction
Assessment of the articulation process  
Articulation analysis can be performed with sustained vowels or with continuous speech signals. The articulation process is assessed primarily through the following:  
* Evaluating resonant cavities within specific frequency bands (formant analysis);
* Speech signal frequency analysis. Formants reflect the physical characteristics of the sound channel (resonant cavity). Different studies have revealed significant differences in the formant frequencies of different vocalized syllables between PD patients and controls [58; 89]. Vowels are formed primarily by movements of the tongue, lips, and jaw, creating oropharyngeal resonating cavities, which amplify certain frequency bands of the voice spectrum. These harmonics are called \"formants\" [60]. The position of the articulators therefore defines the three-dimensional characteristics of the vocal tractus and influences the formant frequencies [59]. Since formants reflect, to some extent, the position of the tongue, a reduction in the articulation extension of this articulator can subsequently affect the frequency range of the formants. The formant location within the frequency axis is closely related to vocal tract resonant frequency values and depends on its shape. The mid-frequency of each formant is different and closely associated with the vocal tract shape. It depends both on the uttered vowel and the individual traits of the speaker. The frequency of the \(F_{1}\) formant is affected by the position of the tongue in the oral cavity. The formant value \(F_{2}\) is determined by the forward-backward movement of the tongue. The \(F_{3}\) and higher formants depend mainly on the length of the vocal tract, while their resonant frequencies change slightly when uttering various vowels [80; 90]. Figure 4 shows the contour of the formants corresponding to patients with PD and healthy subjects. It should be emphasized that diagnostic information can only be sought when analyzing the stability of changes in selected formants and not their sole values, for which, according to claims in the literature, there is a relatively wide frequency range. Please note that the position of the formants on the frequency axis is closely related to vocal tract resonant frequency values and depends on its shape. The mid-frequency of each formant is also closely associated with the vocal tract shape. The waveforms of the formant variability in \(F_{1}\) and \(F_{2}\) demonstrate a significant difference between healthy and PD patients. The waveform for a physiological voice is almost stabilized and has a roughly similar nature to a linear waveform, while when values for a pathological voice do not assume constancy, it is characterized by high variability. Considerable changes for the range of both voices can be observed for the \(F_{3}\) and \(F_{4}\) formants. Less distinctive \"formant\" generation is cause by the reduced range of articulator movements in PD, leading to impaired vowel articulation. The change in the position of the tongue and the characteristics of the cavity will affect the frequencies of formants [89]. Frequency analysis employs spectral parameters to describe the spectral centroid, spectral crest, spectral decrease, spectral entropy, spectral flatness, spectral flux, spectral kurtosis, spectral rolloff point, spectral skewness, spectral slope, spectral spread. These kinds of descriptors give clear information about the spectrum shape. The spectral centroid is a measure that indicates the central frequency or \"balance point\" of a spectrum. The spectral centroid is identified with perceptual properties such as the brightness and sharpness of sound. The spectral crest is a descriptor that defines the so-called spectral ridge signal. In other words, the descriptor measures the relationship between the highest point in a spectrum and the average value of the spectrum [91]. A crest factor of 1 means that there are no peaks. Higher values of this parameter indicate peaks. For example, sound waves tend to have high crest factor values.