{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T21:54:51Z","timestamp":1775253291188,"version":"3.50.1"},"reference-count":38,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/OAPA.html"}],"funder":[{"name":"University of Sharjah through the two competitive research projects entitled \u201cEmotion Recognition in each of Stressful and Emotional Talking Environments Using Artificial Models\u201d","award":["1602040348-P"],"award-info":[{"award-number":["1602040348-P"]}]},{"name":"\u201cCapturing, Studying, and Analyzing Arabic Emirati-Accented Speech Database in Stressful and Emotional Talking Environments for Different Applications\u201d","award":["1602040349-P"],"award-info":[{"award-number":["1602040349-P"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2019]]},"DOI":"10.1109\/access.2019.2901352","type":"journal-article","created":{"date-parts":[[2019,2,25]],"date-time":"2019-02-25T19:50:56Z","timestamp":1551124256000},"page":"26777-26787","source":"Crossref","is-referenced-by-count":118,"title":["Emotion Recognition Using Hybrid Gaussian Mixture Model and Deep Neural Network"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7856-9342","authenticated-orcid":false,"given":"Ismail","family":"Shahin","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1570-0897","authenticated-orcid":false,"given":"Ali Bou","family":"Nassif","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shibani","family":"Hamsa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1186\/1687-4722-2010-862138"},{"key":"ref33","first-page":"5100","article-title":"Analysis of DNN approaches to speaker identification","author":"mat?jka","year":"2016","journal-title":"Proc Int Conf Acoust Speech Signal Process (ICASSP)"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/89.365379"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.specom.2006.11.004"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2008.10.005"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/52.1-2.203"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.2307\/2334776"},{"key":"ref35","author":"hogg","year":"1970","journal-title":"Introduction to Mathematical Statistics"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2896880"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/s10772-014-9251-7"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s00034-016-0284-9"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/NCC.2015.7084826"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s12193-011-0082-4"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s10772-012-9170-4"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.2991\/iccasm.2012.311"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2007.367230"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2011.5947651"},{"key":"ref18","first-page":"223","article-title":"Speech emotion recognition using deep neural network and extreme learning machine","author":"kun","year":"2014","journal-title":"Proc INTERSPEECH"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ACII.2015.7344669"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1515\/jisys-2014-0118"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2005.03.006"},{"key":"ref27","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1109\/TSA.2004.838534","article-title":"Toward detecting emotions in spoken dialogs","volume":"13","author":"lee","year":"2005","journal-title":"IEEE Trans Speech Audio Process"},{"key":"ref3","first-page":"222","article-title":"Emotion recognition in speech signal: Experimental study, development, and application","author":"petrushin","year":"2000","journal-title":"Proc Int Conf Spoken Lang Process"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2015.07.062"},{"key":"ref29","first-page":"101","article-title":"Speech emotion recognition using support vector machines","volume":"6","author":"pan","year":"2012","journal-title":"Int J Smart Home"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-012-9368-5"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.csl.2014.01.003"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2010.2051872"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/79.911197"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2015.2392101"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s10772-011-9125-1"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ACII.2013.58"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ITA.2017.8023477"},{"key":"ref21","article-title":"A research of speech emotion Mathematical recognition based on deep belief network and SVM","volume":"2014","author":"huang","year":"2014","journal-title":"Problems in Engineering"},{"key":"ref24","doi-asserted-by":"crossref","first-page":"1743","DOI":"10.21437\/Eurospeech.1997-494","article-title":"Getting started with SUSAS: A speech under simulated and actual stress database","volume":"4","author":"hansen","year":"1997","journal-title":"Proc Int Conf Speech Commun Technol (EUROSPEECH)"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-018-3760-2"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TASL.2009.2023679"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/s10772-018-9502-0"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08651287.pdf?arnumber=8651287","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,12]],"date-time":"2022-09-12T15:49:17Z","timestamp":1662997757000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8651287\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":38,"URL":"https:\/\/doi.org\/10.1109\/access.2019.2901352","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]}}}