Exploration of glottal characteristics and the vocal folds behavior for the speech under emotion
We preliminarily explore physiological characteristics of the vocal folds when the subject is under different emotional modes. Glottal variations from speech production representing the vocal folds behavior will be mainly discussed. We believe that emotion of the human subject has specific impact on...
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| Published in: | Neurocomputing (Amsterdam) Vol. 410; pp. 328 - 341 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier B.V
14.10.2020
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| ISSN: | 0925-2312, 1872-8286 |
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| Abstract | We preliminarily explore physiological characteristics of the vocal folds when the subject is under different emotional modes. Glottal variations from speech production representing the vocal folds behavior will be mainly discussed. We believe that emotion of the human subject has specific impact on the behavior of the vocal folds, which may result in the variations in glottal flow. This paper investigates the physiological characteristics of the vocal folds through variation in the glottal flow under different emotions. A modified algorithm, Pitch Synchronous Iterative Adaptive Inverse Filtering using Average Magnitude Difference Function based on Empirical Mode Decomposition (AMDFEMD-PSIAIF), is proposed to estimate the glottal flow. Glottal flow is discussed and measured by parameters representing the variations in the vibration behavior of the vocal folds. The physical parameters characterizing the muscle tension and viscosity of the vocal folds are estimated using a speech production model, and a fitting method using the glottal flow is proposed. Through an evaluation on a dataset containing over 1200 voice signals, the glottal and physical parameters are measured to verify the variation mode in vocal folds vibration. We obtain the true positive rate and the average sensitivity of each 9 parameter in 6 different emotional modes. Experimental results show that vocal folds present obvious physical changes when under different emotional modes. The CT muscle of the vocal folds is contracting for fear, happy, angry and surprise mode. The TA is relaxing for happy, angry and sad, while contracting when the speaker is under surprise. Fear and surprise make the surface of the vocal folds sticker, while viscosity reduction occurs when the speaker is experiencing sadness. Therefore, the vibration mechanism and physiological properties of the vocal folds corresponding to emotion modes are preliminarily explored. |
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| AbstractList | We preliminarily explore physiological characteristics of the vocal folds when the subject is under different emotional modes. Glottal variations from speech production representing the vocal folds behavior will be mainly discussed. We believe that emotion of the human subject has specific impact on the behavior of the vocal folds, which may result in the variations in glottal flow. This paper investigates the physiological characteristics of the vocal folds through variation in the glottal flow under different emotions. A modified algorithm, Pitch Synchronous Iterative Adaptive Inverse Filtering using Average Magnitude Difference Function based on Empirical Mode Decomposition (AMDFEMD-PSIAIF), is proposed to estimate the glottal flow. Glottal flow is discussed and measured by parameters representing the variations in the vibration behavior of the vocal folds. The physical parameters characterizing the muscle tension and viscosity of the vocal folds are estimated using a speech production model, and a fitting method using the glottal flow is proposed. Through an evaluation on a dataset containing over 1200 voice signals, the glottal and physical parameters are measured to verify the variation mode in vocal folds vibration. We obtain the true positive rate and the average sensitivity of each 9 parameter in 6 different emotional modes. Experimental results show that vocal folds present obvious physical changes when under different emotional modes. The CT muscle of the vocal folds is contracting for fear, happy, angry and surprise mode. The TA is relaxing for happy, angry and sad, while contracting when the speaker is under surprise. Fear and surprise make the surface of the vocal folds sticker, while viscosity reduction occurs when the speaker is experiencing sadness. Therefore, the vibration mechanism and physiological properties of the vocal folds corresponding to emotion modes are preliminarily explored. |
| Author | Yao, Xiao Hui, Zhijian Ren, Yuqian Liu, Xin Bai, Wensong |
| Author_xml | – sequence: 1 givenname: Xiao surname: Yao fullname: Yao, Xiao organization: The College of IoT Engineering, Hohai University, Changzhou 213000, China – sequence: 2 givenname: Wensong surname: Bai fullname: Bai, Wensong email: wensongb@wustl.edu organization: Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA – sequence: 3 givenname: Yuqian surname: Ren fullname: Ren, Yuqian organization: School of Cyber Science and Engineering, Southeast University, Nanjing, 210000, China – sequence: 4 givenname: Xin surname: Liu fullname: Liu, Xin organization: The College of IoT Engineering, Hohai University, Changzhou 213000, China – sequence: 5 givenname: Zhijian surname: Hui fullname: Hui, Zhijian organization: The College of IoT Engineering, Hohai University, Changzhou 213000, China |
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| Cites_doi | 10.1109/TSP.2010.2097254 10.1109/ICASSP.2016.7472669 10.1016/j.specom.2019.12.001 10.1121/1.427117 10.1109/TASSP.1974.1162598 10.1016/j.jvoice.2019.08.007 10.1016/j.biopsycho.2010.03.010 10.1121/1.424266 10.1159/000263771 10.1109/TASSP.1976.1162800 10.1121/1.397819 10.23919/FRUCT48121.2019.8981498 10.1007/s004050100321 10.1016/j.jvoice.2013.08.006 10.1511/2001.28.344 10.1109/COMSNETS.2019.8711439 10.1177/000348940911800609 10.1109/79.911197 10.1016/j.neuroimage.2016.07.033 10.1109/ACCESS.2018.2860130 10.1007/s12046-011-0041-5 10.1016/0167-6393(92)90005-R 10.1159/000063410 10.1109/CSIE.2009.113 10.1109/89.905995 10.1186/1687-4722-2013-17 10.1109/ACCESS.2019.2936124 10.1121/1.398894 10.1109/MMCS.2009.5256726 10.3109/14015439.2012.679966 10.1159/000151762 10.1016/j.specom.2007.07.002 10.3109/00016489209100797 10.1016/j.neucom.2018.05.005 10.1159/000091405 10.1109/89.622558 10.1109/MSP.2018.2874549 10.15388/NA.2019.5.1 10.1109/ICMLC.2005.1527805 10.1016/0167-6393(95)00040-2 10.1006/jpho.1996.0017 10.1109/APSIPA.2016.7820699 10.1109/ICASSP.2017.7953209 10.1109/LSP.2015.2434732 10.1121/1.1853235 10.1109/ISSPIT.2008.4775670 10.1109/ICOSP.2008.4697464 10.1016/j.jvoice.2017.02.016 10.1109/ICACDOT.2016.7877753 10.1121/1.413569 10.1016/S0892-1997(03)00012-2 10.1016/j.jvoice.2008.04.004 10.1109/TAFFC.2016.2531664 10.1007/978-3-319-31056-5_11 10.1109/eStream.2017.7950316 10.1016/j.chemolab.2018.11.010 |
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| Keywords | Emotion analysis Glottal features Vibration behavior Vocal folds Physiological characteristics |
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