2/2012 - 8 |
Toward Automatic Recognition of Children's Affective State Using Physiological Parameters and Fuzzy Model of EmotionsSCHIPOR, O.-A. , PENTIUC, S.-G. , SCHIPOR, M.-D. |
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Author keywords
assisted speech therapy, emotion recognition, fuzzy model, physiological parameters
References keywords
emotion(11), speech(8), schipor(8), recognition(8), therapy(6), user(5), system(5), pentiuc(5), physiological(4), affect(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2012-05-30
Volume 12, Issue 2, Year 2012, On page(s): 47 - 50
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2012.02008
Web of Science Accession Number: 000305608000008
SCOPUS ID: 84865304575
Abstract
Affective computing - the ability of a system to recognize, understand and simulate human emotional intelligence - is one of the most dynamic fields of HCI - Human Computer Interaction. These characteristics find their applicability in those areas where it is necessary to extend traditional cognitive communication with emotional features. That is why, Computer Based Speech Therapy Systems (CBST), and especially those involving children with speech disorders, require this qualitative shift. So in this paper we propose an original emotional framework recognition as an extension for our previous developed system - Logomon. A fuzzy model is used in order to interpret the values of specific physiological parameters and to obtain the emotional state of the subject. Moreover, an experiment that indicates the emotion pattern (average fuzzy sets) for each therapeutic sequence is also presented. The obtained results encourage us to continue working on automatic emotion recognition and provide important clues regarding the future development of our CBST. |
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[1] Fuzzy Integral and Cuckoo Search Based Classifier Fusion for Human Action Recognition, AYDIN, I., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 1, Volume 18, 2018.
Digital Object Identifier: 10.4316/AECE.2018.01001 [CrossRef] [Full text]
[2] Parkinson's disease Assessment using Fuzzy Expert System and Nonlinear Dynamics, GEMAN, O., TURCU, C. O., GRAUR, A., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 1, Volume 13, 2013.
Digital Object Identifier: 10.4316/AECE.2013.01007 [CrossRef] [Full text]
[3] Software Architecture Design for Spatially-Indexed Media in Smart Environments, SCHIPOR, O.-A., WU, W., TSAI, W.-T., VATAVU, R.-D., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 17, 2017.
Digital Object Identifier: 10.4316/AECE.2017.02003 [CrossRef] [Full text]
[4] GearWheels: A Software Tool to Support User Experiments on Gesture Input with Wearable Devices, Schipor, Ovidiu-Andrei, Vatavu, Radu-Daniel, International Journal of Human–Computer Interaction, ISSN 1044-7318, Issue 18, Volume 39, 2023.
Digital Object Identifier: 10.1080/10447318.2022.2098907 [CrossRef]
[5] SAPIENS, Schipor, Ovidiu-Andrei, Vatavu, Radu-Daniel, Wu, Wenjun, Proceedings of the ACM on Human-Computer Interaction, ISSN 2573-0142, Issue EICS, Volume 3, 2019.
Digital Object Identifier: 10.1145/3331153 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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