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The results showed reasonable accuracy of the neural network in estimating the subglottal pressure in this particular human subject. The neural network was also able to qualitatively differentiate soft and loud speech conditions regarding differences in the subglottal pressure and degree of vocal fold adduction. This simulation-based neural network has potential applications in identifying unhealthy vocal behavior and monitoring progress of voice therapy or vocal training.<\/jats:p>","DOI":"10.1121\/10.0009616","type":"journal-article","created":{"date-parts":[[2022,2,24]],"date-time":"2022-02-24T13:24:47Z","timestamp":1645709087000},"page":"1337-1340","update-policy":"https:\/\/doi.org\/10.1063\/aip-crossmark-policy-page","source":"Crossref","is-referenced-by-count":6,"title":["Estimating subglottal pressure and vocal fold adduction from the produced voice in a single-subject study (L)"],"prefix":"10.1121","volume":"151","author":[{"given":"Zhaoyan","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Head and Neck Surgery, University of California , Los Angeles, 31-24 Rehab Center, 1000 Veteran Avenue, Los Angeles, California 90095-1794, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"231","published-online":{"date-parts":[[2022,2,24]]},"reference":[{"key":"2023081002590078600_c2","doi-asserted-by":"publisher","first-page":"2000111","DOI":"10.1109\/JTEHM.2018.2886021","article-title":"Laryngeal pressure estimation with a recurrent neural network","volume":"7","year":"2019","journal-title":"IEEE J. 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(2016). \u201cAnalysis and synthesis of pathological voice quality,\u201d UCLA Bureau of Glottal Affairs. https:\/\/www.uclahealth.org\/head-neck-surgery\/bga\/software (Last viewed on 1\/28\/2022)."},{"key":"2023081002590078600_c11","first-page":"1846","article-title":"VoiceSauce: A program for voice analysis","year":"2011"},{"key":"2023081002590078600_c12","doi-asserted-by":"publisher","first-page":"4190","DOI":"10.1121\/1.5134784","article-title":"Voice production in a MRI-based subject-specific vocal fold model with parametrically controlled medial surface shape","volume":"146","year":"2019","journal-title":"J. Acoust. Soc. Am."},{"key":"2023081002590078600_c13","doi-asserted-by":"publisher","first-page":"EL264","DOI":"10.1121\/10.0000927","article-title":"Estimation of vocal fold physiology from voice acoustics using machine learning","volume":"147","year":"2020","journal-title":"J. Acoust. Soc. 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