# Real-Time Visual Feedback in Singing Pedagogy: Current Trends and Future Directions
## 3 The Oscillatory Subsystem
### Vocal Folds Contact Variations
The top panel shows EGG shapes with their corresponding derivative (dEGG) for the indicated phonation types. In the middle and lower panels, the waveforms of the indicated phonation types are shown with greater detail, with normalized amplitudes and differentiated by colored lines for comparisons. research applications, it can also be used to map the entire dynamic and pitch range of a voice in real-time. FonaDyn combines the audio and EGG signals to create voice maps of a number of acoustic and EGG metrics and also statistical clustering of these metrics [43]. Figure 9 shows a voice map of the vocal range of a female singer. One normalized EGG shape is also displayed, representing how the contact quotient is calculated by FonaDyn; this corresponds to the total area of the normalized EGG shape during contact, i.e., the contact quotient by integration (\(Q_{\text{cl}}\)) [43]. This EGG metric can be plotted as a voice map. The voice map displays \(Q_{\text{cl}}\) at different combinations of \(f_{\text{o}}\) (horizontal axis) and SPL (vertical axis). The color scale indicates short contacting in blue and long contacting in red. Contact quotient by integration can be used to assess the students' vocal progress. According to previous research, there is a tendency to increase vocal fold contact time and, hence, diminish acoustical losses with training [44]. It should be recalled, however, that an increase in \(p_{\text{sub}}\) also results in an increase in contact time [45], so very long contact times may reflect pressed phonation. Thus, EGG shapes should be interpreted in combination with perceptual evaluations of the corresponding acoustical output. Voice maps can also display other EGG metrics, such as the normalized peak derivative (\(Q_{\Delta}\)) and the index of contacting (\(I_{\text{c}}\)) (Figure 10). The former provides information on the speed of the vocal fold contact: the faster the contact, the louder the voice. The latter combines information from both \(Q_{\text{cl}}\) and \(Q_{\Delta}\), providing a relative indication of vocal fold collision force. It should be noted that this metric has not yet been completely validated, but it is reasonable to assume that a high \(I_{\text{c}}\) (red color in the map) could be related to a high collision impact stress. This is quite important, especially when the target is a more sustainable vocal technique; habitual use of high collision force tends to result in voice disorders [46; 47]. Figure 9: Typical voice map displayed in FonaDyn, showing sound pressure level (SPL) as a function of fundamental frequency (\(f_{\text{o}}\)) for the metric of contact quotient by integration (\(Q_{\text{cl}}\)): (1) Electroglotto-graph (EGG) shape showing the calculation of \(Q_{\text{cl}}\); (2) Real-time voice map of a female singer. Voice maps of EGG metrics using FonaDyn can also visualize phonation types in terms of pre-clustered EGG shapes. These are displayed within the yellow boxes in Figure 11, with the left representing firm (hyperfunctional) and the right representing breathy (hypofunctional) phonation. Singing students can try to model the real-time EGG shape (red boxes) such that they match the pre-clustered EGG shapes. The position of a single point in the pre-recorded voice map can be changed in real-time according to the phonation type. The grey color corresponds to vocalizations previously made to match other intended clustered shapes rather than the one selected as the current model. Building a voice map that corresponds to a voice range profile can be time-consuming, requiring singers to phonate over their entire pitch and dynamic range without leaving large 'holes' in the map. Also, staying on the vowel /a/ is recommended, because modifying the vowel can affect SPL. However, the visualization of voice properties in such a dynamic range of frequencies and intensities can be worthwhile, particularly if the goal is to monitor vocal development. For example, Figure 12 shows voice maps of \(Q_{\Delta}\) and \(I_{\mathrm{c}}\) metrics for an amateur female singer.