## 5 Voice Research and Clinical Applications
Further, the appearance of MW was shown to be a crucial component of the myoelastic-aerodynamic theory of phonation, explaining the mechanisms of the self-sustained vocal fold oscillations. Different singing styles have been analyzed using laryngeal image processing. For instance: the mechanism of the bass type of Mongolian throat singing (called Kargyraa) was studied using FP [154]. They found that both true vocal folds and false vocal folds vibrate during singing; they also observed that the vibration of the false folds adds subharmonics to the acoustic content. In [155] the characteristics of rock singing, also known as distorted singing, were investigated. The authors found some modulations of the vocal folds vibrations by means of periodic or aperiodic motion in the supraglottic mucosa which presumably adds special expressivity to loud and high tones in rock singing. The authors in [156] proposed FP to visualize glottal dynamics during singing sequences consisting in vowels sung at different pitches, different loudness, and exploring the four laryngeal mechanisms. They found additional information on the temporal dynamics of glottal vibratory movements during glottal closing and opening phases. The Laodan and Qingyi role in Peking Opera was studied in [157]. They used image-processing to evaluate glottal changes, relative length of the glottis fissure and relative maximum mucosal amplitude. To understand the vibration of the vocal folds of human voice production at very the high soprano range, several acoustic and glottal parameters are extracted from laryngeal videos [158; 159]. The studies reveal three regions of pitch jumps or instabilities in the high soprano range, above the M1-M2 transition or primo passaggio. They also found that the whole length of the membranous part of the vocal folds took part in the oscillatory process and even at these highest pitches a total closure of the vocal folds was observed. There are also studies devoted to describe properties of laryngeal oscillation patterns with regard to vocal registers and their transitions [160; 161; 41; 160]. In [160] the vocal fold oscillatory patterns during transitions from modal to falsetto register and from modal register to stage voice above the passaggio in professional tenor opera soloists were analyzed using PVG and DKG. They found that the transitions are associated with large modifications of the supraglottic cavities and with retraction of the epiglottis. Therefore, they suggest the use of flexible transnasal high-speed laryngoscopy in order to improve the visibility of vocal folds. In [42] variations of vocal fold vibration patterns were found in the first and the second passaggio. They observed four distinct patterns emerged: smooth transitions with either increasing or decreasing durations of glottal closure, abrupt register transitions, and intermediate loss of vocal fold contact. In addition, laryngeal configuration and vocal fold behavior during different voice quality have been explored in different studies [162; 163]. The results suggests that the voice qualities were produced by independently manipulating the adduction of the artyenoid cartilages and the thickening of the vocal folds. The glottal segmentation and FP have been used to diagnose functional voice disorders [164; 165; 166; 44; 47]. For instance, the authors in [46] presented a computer-aided method for automatically and objectively classifying individuals with normal and abnormal vocal folds vibration patterns. First, a set of image processing techniques were employed to visualize vocal folds dynamics. Later, numerical features were derived, capturing the dynamic behavior and the symmetry of the vocal folds oscillation. Lastly, a support vector machine was applied to classify between normal and pathological vibrations. The results indicate that an objective analysis of abnormal vocal folds vibration can be achieved with considerably high accuracy. The laryngeal imaging techniques have been used to detect early-stage vocal folds cancer.