## 5 Conclusions  
Developing an automated technique for an accurate segmentation of the vocal fold edges from HSV is a crucial prerequisite for the objective analysis of vocal function during connected speech. In the present paper, a new automated technique was introduced to analytically represent the vocal fold edges from HSV data during running speech. The temporal segmentation and the motion compensation approaches used in this work successfully extracted the timestamps of the vocalized segments and localized the vibrating vocal folds of the HSV recording of the \"Rainbow Passage\". Combining an unsupervised ML technique (i.e., k-means clustering) with an ACM approach resulted in a powerful hybrid method for spatial segmentation, which revealed a promising performance in precisely capturing the edges of the vocal folds across frames. This hybrid method helped overcome the limitations of the ACM approach in terms of addressing the dependency of ACM performance to contour initialization, enhancing the edge representation accuracy, mitigating the sensitivity towards image noise, and providing a lower computational cost. The proposed method demonstrated an encouraging performance for challenging HSVdata obtained using a color camera--paving the path toward implementing the hybrid method on less challenging images (monochromatic images) with a higher accuracy and performance. Since the hybrid algorithm was automated, fast, and accurate, it can serve as a promising tool to facilitate the automated analysis and measurement of vocal fold dynamics, especially valuable with the challenges present in the endoscopic analysis of connected speech. Conceptualization, A.M.Y., M.N., D.D.D., and R.F.O. ; methodology, A.M.Y. and M.N. ; software, A.M.Y. and M.N. ; formal analysis, A.M.Y. and M.N. ; investigation, A.M.Y., M.N., D.D.D., S.R.C.Z. and A.d.A. ; resources, M.N., D.D.D., S.R.C.Z., A.d.A., and R.F.O. ; writing--original draft preparation, A.M.Y. and M.N. ; writing--review and editing, M.N., D.D.D., S.R.C.Z., A.d.A., and R.F.O. ; supervision, M.N. ; funding acquisition, M.N. and D.D.D. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Institutes of Health, NIDCD, K01 DC017751 \"Studying the Laryngeal Mechanisms Underlying Dysphonia in Connected Speech\" and NIDCD R01-DC007640 \"Efficacy of Laryngeal High-Speed Videoendoscopy.\"  
The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Boards of Cincinnati Children's Hospital Medical Center (protocol code 2012-1138, 15 October 2014) and Michigan State University (IRB# x17-1613e, 30 November 2017). Informed Consent Statement: Informed consent was obtained from the subject involved in the study. Data Availability Statement: Data from this study can be made available upon request to the corresponding author after executing appropriate data sharing agreement. The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. References  
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