This proposal aims to employ the recent advancement of coupling fiberoptic endoscopes with high-speed videoendoscopy (HSV) systems to obtain HSV recordings during connected speech. The goal is to study vocal mechanisms underlying dysphonia in patients with neurogenic voice disorders. The long-term goal of this line of research is to create clinically applicable quantitative methods for functional measurement of vocal fold vibration in connected speech using innovative laryngeal imaging, an approach that could advance clinical voice assessment and treatment practice.
In Aim 1, HSV-based measures of vocal fold kinematics will be developed and the influence of these measures on voice audio-perceptual qualities in the patients will be determined. Image processing techniques will be developed to extract such measures from the HSV data in connected speech. The extracted measures will be given as inputs to the statistical models to determine the source of the differences between the normal controls and the patients for different speech phonetic contexts and words.
This aim provides an unbiased HSV-based method to predict voice quality. Developing such HSV-based methodology for functional laryngeal examination in connected speech can enhance clinical voice assessment. In addition, better understanding the influence of phonetic context would lead to optimizing the protocols for functional voice assessment through laryngeal imaging in connected speech.
In Aim 2, machine learning approaches will be employed to discover hidden physics and unknown laryngeal mechanisms of voice production in the dysphonic patients. The findings of this project will help make necessary adjustments in biomechanical or physiological characteristics of vocal folds to enhance voice quality in patients with neurogenic voice disorders. Therefore, the outcome of this research will aid clinicians in properly selecting, and developing new treatment strategies (therapeutic, medicinal, or surgical), which are based on the gained knowledge of laryngeal mechanisms of dysphonia. The proposed research is in harmony with multiple priority areas of the NIDCD, described in the 2017-2021 Strategic Plan.
Both aims support Priority 3 (improve methods of diagnosis, treatment, and prevention) through developing objective HSV-based measures and predicting the voice quality. Comparing laryngeal mechanisms in normal and disordered voices addresses Priority 1 (deepen our understanding of the normal function of the systems of human communication).
Both aims propose to study laryngeal mechanisms in patients with neurogenic and functional voice disorders, which addresses Priority 2 (increase our knowledge about conditions that alter or diminish communication and health).
The goal of this proposal is to determine laryngeal mechanisms underlying dysphonia in connected speech, which will lead to development of clinically applicable quantitative methods for functional laryngeal examination in connected speech using laryngeal imaging. This can potentially result in enhancement of clinical voice assessment and development of new clinical voice management strategies to better help people with voice disorders.