{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T01:34:18Z","timestamp":1777426458855,"version":"3.51.4"},"reference-count":27,"publisher":"SAGE Publications","issue":"9","license":[{"start":{"date-parts":[[2016,7,20]],"date-time":"2016-07-20T00:00:00Z","timestamp":1468972800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Ann Otol Rhinol Laryngol"],"published-print":{"date-parts":[[2016,9]]},"abstract":"<jats:sec>\n                    <jats:title>Objectives:<\/jats:title>\n                    <jats:p>Loss of speech following tracheostomy and laryngectomy severely limits communication to simple gestures and facial expressions that are largely ineffective. To facilitate communication in these patients, we seek to develop a low-cost, noninvasive, portable, and simple visual speech recognition program (VSRP) to convert articulatory facial movements into speech.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>A Microsoft Kinect\u2013based VSRP was developed to capture spatial coordinates of lip movements and translate them into speech. The articulatory speech movements associated with 12 sentences were used to train an artificial neural network classifier. The accuracy of the classifier was then evaluated on a separate, previously unseen set of articulatory speech movements.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>The VSRP was successfully implemented and tested in 5 subjects. It achieved an accuracy rate of 77.2% (65.0%-87.6% for the 5 speakers) on a 12-sentence data set. The mean time to classify an individual sentence was 2.03 milliseconds (1.91-2.16).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>We have demonstrated the feasibility of a low-cost, noninvasive, portable VSRP based on Kinect to accurately predict speech from articulation movements in clinically trivial time. This VSRP could be used as a novel communication device for aphonic patients.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/0003489416650689","type":"journal-article","created":{"date-parts":[[2016,5,22]],"date-time":"2016-05-22T14:57:39Z","timestamp":1463929059000},"page":"752-757","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["Development of a Low-Cost, Noninvasive, Portable Visual Speech Recognition Program"],"prefix":"10.1177","volume":"125","author":[{"given":"Gavriel D.","family":"Kohlberg","sequence":"first","affiliation":[{"name":"Department of Otolaryngology\u2013Head and Neck Surgery, Columbia University College of Physicians and Surgeons, New York, New York, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ya\u2019akov (Kobi)","family":"Gal","sequence":"additional","affiliation":[{"name":"Department of Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anil K.","family":"Lalwani","sequence":"additional","affiliation":[{"name":"Department of Otolaryngology\u2013Head and Neck Surgery, Columbia University College of Physicians and Surgeons, New York, New York, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2016,7,20]]},"reference":[{"key":"bibr1-0003489416650689","doi-asserted-by":"publisher","DOI":"10.1016\/j.otc.2008.09.010"},{"key":"bibr2-0003489416650689","doi-asserted-by":"publisher","DOI":"10.1016\/j.apnr.2005.09.006"},{"key":"bibr3-0003489416650689","doi-asserted-by":"publisher","DOI":"10.1097\/00003246-200204000-00004"},{"key":"bibr4-0003489416650689","doi-asserted-by":"publisher","DOI":"10.1177\/0194599812438170"},{"key":"bibr5-0003489416650689","doi-asserted-by":"publisher","DOI":"10.1007\/s00268-003-7107-4"},{"key":"bibr6-0003489416650689","doi-asserted-by":"publisher","DOI":"10.1055\/s-0030-1255340"},{"key":"bibr7-0003489416650689","doi-asserted-by":"publisher","DOI":"10.1186\/1477-7525-6-26"},{"key":"bibr8-0003489416650689","doi-asserted-by":"publisher","DOI":"10.1080\/13548500600665542"},{"key":"bibr9-0003489416650689","doi-asserted-by":"publisher","DOI":"10.1016\/j.otc.2004.01.006"},{"key":"bibr10-0003489416650689","doi-asserted-by":"publisher","DOI":"10.4103\/0019-509X.75841"},{"key":"bibr11-0003489416650689","doi-asserted-by":"crossref","unstructured":"Kaufman M. Medicare TEP policy hurts providers, patients. The ASHA Leader. 2014;19:30. http:\/\/leader.pubs.asha.org\/article.aspx?articleid=1901964. Accessed July 15, 2015.","DOI":"10.1044\/leader.PA2.19092014.30"},{"key":"bibr12-0003489416650689","doi-asserted-by":"publisher","DOI":"10.1016\/j.hrtlng.2003.12.005"},{"key":"bibr13-0003489416650689","doi-asserted-by":"publisher","DOI":"10.1310\/tsr1504-384"},{"key":"bibr14-0003489416650689","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.1996.543246"},{"key":"bibr15-0003489416650689","first-page":"295","volume":"2011","author":"Wand M","year":"2011","journal-title":"Biosignals"},{"key":"bibr16-0003489416650689","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2012.6289039"},{"key":"bibr17-0003489416650689","unstructured":"3D electromagnetic articulograph carstens medizinelektronik GmbH. http:\/\/www.articulograph.de\/. Accessed september 24, 2015."},{"key":"bibr18-0003489416650689","unstructured":"Wang J, Samal A, Green JR, Rudzicz F. 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