{"doi":"10.61782/fa.2023.1124","title":"Applications of Machine Learning for Vocal Fold Motion Analysis using Laryngeal High-Speed Videoendoscopy","abstract":"Laryngeal imaging is widely used to investigate anatomical and physiological aspects of voice production.Laryngeal high-speed videoendoscopy (HSV) is a laryngeal imaging technique and a powerful tool enabling us to capture the vibratory details of vocal folds in each cycle of vibration.HSV is specifically useful for studying voice production in connected speech, where non-stationary and transitory behaviors of vocal folds are consistently observed.This capability of HSV becomes more valuable when studying voice disorders, which involve more irregular and nonstationary behaviors of vocal folds.In this work, HSV is used to study neurogenic voice disorders and compare them with normophonic voices.The HSV data were obtained from the speakers during production of connected speech.The data were collected using a monochrome high-speed camera coupled with a flexible nasolaryngoscope.The dataset for each participant contains hundreds of thousands of images, therefore, machine learning is used for the analysis of this big dataset.The results show that the machine learning approach is successful in the analysis of HSV data with high levels of accuracy.","journal":null,"year":2022,"id":302414,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9598,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":464924,"name":"Thomas R. Henry","orcid":"0000-0002-5708-903X","position":1,"is_corresponding":false},{"id":994424,"name":"Ahmed Mohamed Fahmy Yousef","orcid":"0000-0003-0522-0734","position":2,"is_corresponding":false},{"id":743552,"name":"Mohsen Zayernouri","orcid":"0000-0002-0831-2610","position":3,"is_corresponding":false},{"id":362701,"name":"Stephanie R. C. Zacharias","orcid":null,"position":4,"is_corresponding":false},{"id":361105,"name":"Dimitar D. Deliyski","orcid":"0000-0002-9025-6047","position":5,"is_corresponding":false},{"id":361108,"name":"Maryam Naghibolhosseini","orcid":"0000-0002-7310-8456","position":0,"is_corresponding":true}],"reference_count":32,"raw_metadata":null,"created_at":"2026-07-19T00:32:16.279991Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}