Bimodal emotion recognition
Abstract
This paper describes the use of statistical techniques and hidden Markov models (HMM) in the recognition of emotions. The method aims to classify 6 basic emotions (anger, dislike, fear, happiness, sadness and surprise) from both facial expressions (video) and emotional speech (audio). The emotions of 2 human subjects were recorded and analyzed. The findings show that the audio and video information can be combined using a rule-based system to improve the recognition rate.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Relatively few efforts have focused on emotion recognition using both facial expressions and acoustic information.
“Although several automatic emotion recognition systems have explored the use of either facial expressions [1],[11],[16],[21],[22] or speech [9],[18],[14] to detect human affective states, relatively few efforts have focused on emotion recognition using both modalities [4],[8].”
From Analysis of emotion recognition using facial expressions, speech and multimodal information (2004) · cites this paper as [8]
None of the previous papers attempted to compare which fusion approach is more suitable for emotion recognition.
“However, none of these papers attempted to compare which fusion approach is more suitable for emotion recognition.”
From Analysis of emotion recognition using facial expressions, speech and multimodal information (2004) · cites this paper as [8]
The performance of emotion recognition systems can be improved by the use of multimodal information.
“All these studies have shown that the performance of emotion recognition systems can be improved by the use of multimodal information.”
From Analysis of emotion recognition using facial expressions, speech and multimodal information (2004) · cites this paper as [8]
Cites
Strong evidence for universals in facial expressions: A reply to Russell's mistaken critique.
Ekman, P. (1994) · Psychological Bulletin · doi:10.1037//0033-2909.115.2.268 · Cited by 1,130 · see citing works
A computational framework and an algorithm for the measurement of visual motion
Anandan, P. (1989) · International Journal of Computer Vision · doi:10.1007/bf00158167 · Cited by 1,073 · see citing works
Mehrabian, A. (2017) · communication theory · doi:10.4324/9781315080918-15 · Cited by 879 · see citing works
Super resolution pitch determination of speech signals
Medan, Y., Yair, E., & Chazan, D. (1991) · IEEE Transactions on Signal Processing · doi:10.1109/78.80763 · Cited by 198 · see citing works
Multimodal human emotion/expression recognition
Chen, L. S., Huang, T. S., Miyasato, T., & Nakatsu, R. (2002) · Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition · doi:10.1109/afgr.1998.670976 · Cited by 183 · see citing works
Yoshitomi, Y., Kim, S.-I., Kawano, T., & Kilazoe, T. (2002) · Proceedings 9th IEEE International Workshop on Robot and Human Interactive Communication. IEEE RO-MAN 2000 (Cat. No.00TH8499) · doi:10.1109/roman.2000.892491 · Cited by 144 · see citing works
Modeling Multimodal Expression of User’s Affective Subjective Experience
Bianchi‐Berthouze, N., & Lisetti, C. (2002) · User Modeling and User-Adapted Interaction · doi:10.1023/a:1013365332180 · Cited by 96 · see citing works
Boosted learning in dynamic bayesian networks for multimodal speaker detection
Garg, A., Pavlović, V., & Rehg, J. M. (2003) · Proceedings of the IEEE · doi:10.1109/jproc.2003.817119 · Cited by 51 · see citing works
Affective intelligence — the missing link?
Picard, R. W., & Cosier, G. (1997) · BT Technology Journal · doi:10.1023/a:1018643815520 · Cited by 27 · see citing works
Use of Multimodal Information in Facial Emotion Recognition
Silva, L. C. D., Miyasato, T., & Nakatsu, R. (1998) · IEICE Transactions on Information and Systems · Cited by 22 · see citing works
Affective Intelligence — The Missing Link?
Picard, R. W., & Cosier, G. (1999) · Springer eBooks · doi:10.1007/978-1-4615-5291-8_13 · Cited by 6 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Multimodal human–computer interaction: A survey
Jaimes, A., & Sebe, N. (2007) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2006.10.019 · Cited by 965 · see citing works
Analysis of emotion recognition using facial expressions, speech and multimodal information
Busso, C., Deng, Z., Yildirim, S., Bulut, M., Lee, C. M., Kazemzadeh, A., Lee, S., Neumann, U., & Narayanan, S. (2004) · Proceedings of the 6th international conference on Multimodal interfaces · doi:10.1145/1027933.1027968 · Cited by 840 · see citing works
Toward an affect-sensitive multimodal human-computer interaction
Pantic, M., & Rothkrantz, L. J. M. (2003) · Proceedings of the IEEE · doi:10.1109/jproc.2003.817122 · Cited by 791 · see citing works
Corneanu, C. A., Simon, M. O., Cohn, J. F., & Guerrero, S. E. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2515606 · Cited by 527 · see citing works
ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection
Hazarika, D., Poria, S., Mihalcea, R. F., Cambria, E., & Zimmermann, R. (2018) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d18-1280 · Cited by 465 · see citing works
Music emotion recognition: A state of the art review
Kim, Y. E., Schmidt, E. M., Migneco, R., Morton, B. G., Richardson, P., Scott, J. J., Speck, J. A., & Turnbull, D. (2010) · Digital Collections - Ithaca College Library (Ithaca College) · Cited by 402 · see citing works
Wu, C., & Liang, W.-B. (2010) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2010.16 · Cited by 265 · see citing works
Emotion detection from text and speech: a survey
Sailunaz, K., Dhaliwal, M., Rokne, J. G., & Alhajj, R. (2018) · Social Network Analysis and Mining · doi:10.1007/s13278-018-0505-2 · Cited by 264 · see citing works
Lopatovska, I., & Arapakis, I. (2010) · Information Processing & Management · doi:10.1016/j.ipm.2010.09.001 · Cited by 261 · see citing works
Emotion recognition from text using semantic labels and separable mixture models
Wu, C., Chuang, Z.-J., & Lin, Y.-C. (2006) · ACM Transactions on Asian Language Information Processing · doi:10.1145/1165255.1165259 · Cited by 244 · see citing works
Affective multimodal human-computer interaction
Pantic, M., Sebe, N., Cohn, J. F., & Huang, T. (2005) · Proceedings of the 13th annual ACM international conference on Multimedia · doi:10.1145/1101149.1101299 · Cited by 234 · see citing works
Kumar, A., Srinivasan, K., Cheng, W.-H., & Zomaya, A. Y. (2019) · Information Processing & Management · doi:10.1016/j.ipm.2019.102141 · Cited by 214 · see citing works
Recognizing Human Emotional State From Audiovisual Signals
Wang, Y., & Guan, L. (2008) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2008.921734 · Cited by 213 · see citing works
Emotion Recognition Based on Joint Visual and Audio Cues
Sebe, N., Cohen, I., Gevers, T., & Huang, T. S. (2006) · 18th International Conference on Pattern Recognition (ICPR'06) · doi:10.1109/icpr.2006.489 · Cited by 202 · see citing works
Recognizing Human Emotional State From Audiovisual Signals*
Wang, Y., & Guan, L. (2008) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2008.927665 · Cited by 202 · see citing works
MULTIMODAL EMOTION RECOGNITION
Sebe, N., Cohen, I., & Huang, T. S. (2005) · Handbook of Pattern Recognition and Computer Vision · doi:10.1142/9789812775320_0021 · Cited by 201 · see citing works
Affect Recognition from Face and Body: Early Fusion vs. Late Fusion
Gunes, H., & Piccardi, M. (2006) · 2005 IEEE International Conference on Systems, Man and Cybernetics · doi:10.1109/icsmc.2005.1571679 · Cited by 191 · see citing works
Shoumy, N. J., Ang, L.-M., Seng, K. P., Rahaman, D. M. M., & Zia, T. (2020) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2019.102447 · Cited by 171 · see citing works
Multimodal information fusion application to human emotion recognition from face and speech
Mansoorizadeh, M., & Charkari, N. M. (2009) · Multimedia Tools and Applications · doi:10.1007/s11042-009-0344-2 · Cited by 164 · see citing works
A survey of speech emotion recognition in natural environment
Fahad, M. S., Ranjan, A., Yadav, J., & Deepak, A. (2020) · Digital Signal Processing · doi:10.1016/j.dsp.2020.102951 · Cited by 162 · see citing works
Exploring Fusion Methods for Multimodal Emotion Recognition with Missing Data
Wagner, J., Andre, E., Lingenfelser, F., & Kim, J. (2011) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2011.12 · Cited by 156 · see citing works
Multimodal approaches for emotion recognition: a survey
Sebe, N., Cohen, I., Gevers, T., & Huang, T. S. (2005) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.600746 · Cited by 154 · see citing works
Kalateh, S., Estrada-Jimenez, L. A., Nikghadam-Hojjati, S., & Barata, J. (2024) · IEEE Access · doi:10.1109/access.2024.3430850 · Cited by 151 · see citing works
Bimodal Emotion Recognition using Speech and Physiological Changes
Kim, J. (2007) · doi:10.5772/4754 · Cited by 145 · see citing works
Audio-Visual Affect Recognition
Zeng, Z., Tu, J., Liu, M., Huang, T. S., Pianfetti, B., Roth, D., & Levinson, S. (2007) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2006.886310 · Cited by 135 · see citing works
Audio–Visual Affective Expression Recognition Through Multistream Fused HMM
Zeng, Z., Tu, J., Pianfetti, B., & Huang, T. S. (2008) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2008.921737 · Cited by 134 · see citing works
Modeling naturalistic affective states via facial and vocal expressions recognition
Caridakis, G., Malatesta, L., Kessous, L., Amir, N., Raouzaiou, A. T., & Karpouzis, K. C. (2006) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1145/1180995.1181029 · Cited by 133 · see citing works
Audiovisual Information Fusion in Human–Computer Interfaces and Intelligent Environments: A Survey
Shivappa, S. T., Trivedi, M. M., & Rao, B. D. (2010) · Proceedings of the IEEE · doi:10.1109/jproc.2010.2057231 · Cited by 127 · see citing works
A user-independent real-time emotion recognition system for software agents in domestic environments
Leon, E., Clarke, G., Callaghan, V., & Sepulveda, F. (2006) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2006.06.001 · Cited by 124 · see citing works
Emotion recognition in speech using MFCC and wavelet features
Kolli, V. K. K., & Satish, P. (2013) · IEEE International Advance Computing Conference · doi:10.1109/iadcc.2013.6514336 · Cited by 122 · see citing works
Multi-Modal Emotion Recognition from Speech and Text
Chuang, Z.-J., & Wu, C. (2004) · Cited by 117 · see citing works
Multimodal Human Computer Interaction: A Survey
Jaimes, A., & Sebe, N. (2005) · Lecture notes in computer science · doi:10.1007/11573425_1 · Cited by 115 · see citing works
EEG-based Emotion Recognition Using Self-Organizing Map for Boundary Detection
Khosrowabadi, R., Quek, C. H., Wahab, A., & Ang, K. K. (2010) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2010.1031 · Cited by 113 · see citing works
Towards Text-based Emotion Detection A Survey and Possible Improvements
Kao, E. C.-C., Liu, C.-C., Yang, T., Hsieh, C.-T., & Soo, V. (2009) · International Conference on Information Management and Engineering (ICIME) · doi:10.1109/icime.2009.113 · Cited by 110 · see citing works
Emotion Recognition from Text Based on Automatically Generated Rules
Shaheen, S. I., El-Hajj, W., Hajj, H. M., & Elbassuoni, S. (2014) · IEEE ... International Conference on Data Mining workshops · doi:10.1109/icdmw.2014.80 · Cited by 108 · see citing works
A hybrid latent space data fusion method for multimodal emotion recognition
Nemati, S., Rohani, R., Basiri, M. E., Abdar, M., Yen, N. Y., & Makarenkov, V. (2019) · IEEE Access · doi:10.1109/access.2019.2955637 · Cited by 98 · see citing works
Meng, H., Bianchi‐Berthouze, N., Deng, Y. S., Cheng, J., & Cosmas, J. (2015) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2015.2418092 · Cited by 94 · see citing works
A Combined Rule-Based & Machine Learning Audio-Visual Emotion Recognition Approach
Seng, K. P., Ang, L.-M., & Ooi, C. S. (2016) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2016.2588488 · Cited by 91 · see citing works
Bejani, M., Gharavian, D., & Charkari, N. M. (2012) · Neural Computing and Applications · doi:10.1007/s00521-012-1228-3 · Cited by 77 · see citing works
Kindergarten social assistive robot: First meeting and ethical issues
Fridin, M. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2013.09.005 · Cited by 76 · see citing works
Affective State Level Recognition in Naturalistic Facial and Vocal Expressions
Meng, H., & Bianchi‐Berthouze, N. (2013) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2013.2253768 · Cited by 75 · see citing works
Modeling Naturalistic Affective States Via Facial, Vocal, and Bodily Expressions Recognition
Karpouzis, K. C., Caridakis, G., Kessous, L., Amir, N., Raouzaiou, A. T., Malatesta, L., & Kollias, S. (2007) · Springer eBooks · doi:10.1007/978-3-540-72348-6_5 · Cited by 72 · see citing works
Audio-visual emotion recognition using an emotion space concept
Kanluan, I., Grimm, M., & Kroschel, K. (2008) · Cited by 66 · see citing works
Bimodal HCI-related affect recognition
Zeng, Z., Tu, J., Liu, M., Zhang, T., Rizzolo, N., Zhang, Z., Huang, T. S., Roth, D., & Levinson, S. E. (2004) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1145/1027933.1027958 · Cited by 63 · see citing works
Emotion recognition from the facial image and speech signal
Go, H.-J., Kwak, K.-C., Lee, D.-J., & Chun, M.-G. (2003) · Cited by 63 · see citing works
Audio-Visual Affect Recognition through Multi-Stream Fused HMM for HCI
Zeng, Z., Tu, J., Pianfetti, B., Liu, M., Zhang, T., Zhang, Z., Huang, T. S., & Levinson, S. (2005) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2005.77 · Cited by 62 · see citing works
Integrating information from speech and physiological signals to achieve emotional sensitivity
Kim, J., André, E., Rehm, M., Vogt, T., & Wagner, J. (2005) · Interspeech (USB) · doi:10.21437/interspeech.2005-380 · Cited by 62 · see citing works
Emotion recognition using acoustic features and textual content
Chuang, Z.-J., & Wu, C. (2005) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme.2004.1394123 · Cited by 62 · see citing works
Comparison of Different Classifiers for Emotion Recognition
Iliou, T., & Anagnostopoulos, C. (2009) · Panhellenic Conference on Informatics · doi:10.1109/pci.2009.7 · Cited by 58 · see citing works
Polarity and Intensity: the Two Aspects of Sentiment Analysis
Tian, L., Lai, C., & Moore, J. D. (2018) · doi:10.18653/v1/w18-3306 · Cited by 58 · see citing works
Yang, E., & Dorneich, M. C. (2017) · International Journal of Social Robotics · doi:10.1007/s12369-017-0407-x · Cited by 52 · see citing works
A robust multimodal approach for emotion recognition
Song, M., You, M., Li, N., & Chen, C. (2008) · Neurocomputing · doi:10.1016/j.neucom.2007.07.041 · Cited by 52 · see citing works
Audio-Visual Spontaneous Emotion Recognition
Zeng, Z., Hu, Y., Roisman, G. I., Wen, Z., Fu, Y., & Huang, T. S. (2007) · Springer eBooks · doi:10.1007/978-3-540-72348-6_4 · Cited by 51 · see citing works
Statistical Evaluation of Speech Features for Emotion Recognition
Iliou, T., & Anagnostopoulos, C. (2009) · International Conference on Digital Telecommunications (ICDT) · doi:10.1109/icdt.2009.30 · Cited by 50 · see citing works
Nuha, N. S., Mahmud, T., Rezaoana, N., Hossain, M. S., & Andersson, K. (2023) · IEEE International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE) · doi:10.1109/wiecon-ece60392.2023.10456488 · Cited by 49 · see citing works
Emotion Recognition Using Physiological and Speech Signal in Short-Term Observation
Kim, J., & André, E. (2006) · Lecture notes in computer science · doi:10.1007/11768029_6 · Cited by 48 · see citing works
Robotics Agent Coacher for CP motor Function (RAC CP Fun)
Fridin, M., & Belokopytov, M. (2014) · Robotica · doi:10.1017/s026357471400174x · Cited by 45 · see citing works
Bahreini, K., Nadolski, R. J., & Westera, W. (2016) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2016.1159799 · Cited by 45 · see citing works
Video Analytics for Customer Emotion and Satisfaction at Contact Centers
Seng, K. P., & Ang, L.-M. (2017) · IEEE Transactions on Human-Machine Systems · doi:10.1109/thms.2017.2695613 · Cited by 45 · see citing works
Gharavian, D., Bejani, M., & Sheikhan, M. (2016) · Multimedia Tools and Applications · doi:10.1007/s11042-015-3180-6 · Cited by 44 · see citing works
Multimodal user’s affective state analysis in naturalistic interaction
Caridakis, G., Karpouzis, K. C., Wallace, M., Kessous, L., & Amir, N. (2009) · Journal on Multimodal User Interfaces · doi:10.1007/s12193-009-0030-8 · Cited by 38 · see citing works
Deception detection using multimodal fusion approaches
Chebbi, S., & Jebara, S. B. (2021) · Multimedia Tools and Applications · doi:10.1007/s11042-021-11148-9 · Cited by 36 · see citing works
The dynamic emotion recognition system based on functional connectivity of brain regions
Khosrowabadi, R., Heijnen, M., Wahab, A., & Quek, C. H. (2010) · IEEE Intelligent Vehicles Symposium · doi:10.1109/ivs.2010.5548102 · Cited by 35 · see citing works
Multimodal information fusion for selected multimedia applications
Guan, L., Wang, Y., Zhang, R., Tie, Y., Bulzacki, A., & Ibrahim, M. (2010) · International Journal of Multimedia Intelligence and Security · doi:10.1504/ijmis.2010.035969 · Cited by 34 · see citing works
The Effect of Time Delay on Emotion, Arousal, and Satisfaction in Human-Robot Interaction
Yang, E., & Dorneich, M. C. (2015) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1541931215591094 · Cited by 33 · see citing works
Recognition of Emotional States in Natural Human-Computer Interaction
Cowie, R., Douglas‐Cowie, E., Karpouzis, K. C., Caridakis, G., Wallace, M., & Kollias, S. (2008) · Springer eBooks · doi:10.1007/978-3-540-78345-9_6 · Cited by 33 · see citing works
Learning polite behavior with situation models
Barraquand, R., & Crowley, J. L. (2008) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/1349822.1349850 · Cited by 32 · see citing works
Building a three-level multimodal emotion recognition framework
Garcia-Garcia, J. M., Lozano, M. D., Penichet, V. M. R., & Law, E. L. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-13254-8 · Cited by 32 · see citing works
Güneş, H., & Piccardi, M. (2005) · Lecture notes in computer science · doi:10.1007/11573548_14 · Cited by 32 · see citing works
Face and Body Gesture Recognition for a Vision-Based Multimodal Analyzer.
Güneş, H., Piccardi, M., & Jan, T. (2003) · Cited by 31 · see citing works
Affective computation on EEG correlates of emotion from musical and vocal stimuli
Khosrowabadi, R., Wahab, A., Ang, K. K., & Baniasad, M. H. (2009) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2009.5178748 · Cited by 31 · see citing works
Affect-aware behaviour modelling and control inside an intelligent environment
Leon, E., Clarke, G., Callaghan, V., & Doctor, F. (2010) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2009.12.002 · Cited by 30 · see citing works
Unobtrusive Multimodal Emotion Detection in Adaptive Interfaces: Speech and Facial Expressions
Truong, K. P., van Leeuwen, D. A., & Neerincx, M. A. (2007) · Lecture notes in computer science · doi:10.1007/978-3-540-73216-7_40 · Cited by 30 · see citing works
PAD-based multimodal affective fusion
Gilroy, S. W., Cavazza, M., Niiranen, M., André, E., Vogt, T., Urbain, J., Benayoun, M., Seichter, H., & Billinghurst, M. (2009) · International Conference on Affective Computing and Intelligent Interaction and workshops · doi:10.1109/acii.2009.5349552 · Cited by 28 · see citing works
Visual/Acoustic Emotion Recognition
Chen, C., Huang, Y.-K., & Cook, P. R. (2005) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme.2005.1521709 · Cited by 28 · see citing works
Emotion Recognition from EEG and Facial Expressions: a Multimodal Approach
Chaparro, V., Gomez, A., Salgado, A., Quintero, O. L., Lopez, N., & Villa, L. F. (2018) · 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2018.8512407 · Cited by 27 · see citing works
(2012) · The turkish online journal of educational technology · Cited by 27 · see citing works
Multimodal Affect Analysis for Product Feedback AssessmentPreprint
Patwardhan, A., & Knapp, G. M. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1705.02694 · Cited by 26 · see citing works
SVM-MLP-PNN Classifiers on Speech Emotion Recognition Field - A Comparative Study
Iliou, T., & Anagnostopoulos, C. (2010) · International Conference on Digital Telecommunications (ICDT) · doi:10.1109/icdt.2010.8 · Cited by 21 · see citing works
A Multilevel Fusion Approach for Audiovisual Emotion Recognition
Chetty, G., Wagner, M., & Goecke, R. (2015) · Wiley eBooks · doi:10.1002/9781118910566.ch17 · Cited by 21 · see citing works
Multimodal emotion recognition using SDA-LDA algorithm in video clips
Tiwari, P., Rathod, H., Thakkar, S., & Darji, A. D. (2021) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-021-03529-7 · Cited by 20 · see citing works
Bokhare, A., & Kothari, T. (2023) · SN Computer Science · doi:10.1007/s42979-022-01619-7 · Cited by 20 · see citing works
Emotion Recognition from Text based on the Rough Set Theory and the Support Vector Machines
Teng, Z., Ren, F., & Kuroiwa, S. (2007) · International Conference on Natural Language Processing and Knowledge Engineering (NLPKE) · doi:10.1109/nlpke.2007.4368008 · Cited by 20 · see citing works
Human well-being and flowing work in an intelligent work environment
Reijula, J., Gröhn, M., Müller, K., & Reijula, K. E. (2011) · Intelligent Buildings International · doi:10.1080/17508975.2011.608837 · Cited by 20 · see citing works
Emotion Recognition in Gamers Wearing Head-mounted Display
Yong, H., Lee, J., & Choi, J. (2019) · IEEE Conference on Virtual Reality and 3D User Interfaces (VR) · doi:10.1109/vr.2019.8797736 · Cited by 20 · see citing works
Emotion Recognition from Speech: A Survey
Δρακόπουλος, Γ., Pikramenos, G., Evaggelos Spyrou, A., & Perantonis, S. J. (2019) · International Conference on Web Information Systems and Technologies · doi:10.5220/0008495004320439 · Cited by 20 · see citing works
Toward Constructing A Multilingual Speech Corpus for Taiwanese (Min-nan), Hakka, and Mandarin
Lyu, R.-Y., Liang, M.-S., & Chiang, Y.-C. (2004) · doi:10.30019/ijclclp.200408.0001 · Cited by 20 · see citing works
Audiovisual emotion recognition
Silva, L. C. D. (2005) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/icsmc.2004.1398373 · Cited by 19 · see citing works
Towards Emotion Recognition from Speech: Definition, Problems and the Materials of Research
Anagnostopoulos, C., & Iliou, T. (2010) · Studies in computational intelligence · doi:10.1007/978-3-642-11684-1_8 · Cited by 18 · see citing works
Multimodal Approach to Emotion Recognition for Enhancing Human Machine Interaction - A Survey
Veni, S., & Thushara, S. (2017) · International Journal on Advanced Science Engineering and Information Technology · doi:10.18517/ijaseit.7.4.1662 · Cited by 17 · see citing works
A Sensor Technology Survey for a Stress-Aware Trading Process
Fernández, J., Augusto, J. C., Seepold, R., & Madrid, N. M. (2012) · IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) · doi:10.1109/tsmcc.2011.2179028 · Cited by 17 · see citing works
Alam, M. A. U., Roy, N., Gangopadhyay, A., & Galik, E. M. (2016) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2016.06.015 · Cited by 17 · see citing works
Emotion Recognition from Persian Speech with Neural Network
Hamidi, M. (2012) · International Journal of Artificial Intelligence & Applications · doi:10.5121/ijaia.2012.3509 · Cited by 16 · see citing works
Computer Vision Systems for “Context-Aware” Active Vehicle Safety and Driver Assistance
Boyraz, P., Yang, X., & Hansen, J. H. L. (2011) · Springer eBooks · doi:10.1007/978-1-4419-9607-7_15 · Cited by 16 · see citing works
Introduction to Emotion Recognition
Konar, A., Halder, A., & Chakraborty, A. (2015) · Wiley eBooks · doi:10.1002/9781118910566.ch1 · Cited by 16 · see citing works
Bimodal information analysis for emotion recognition
Meghjani, M., Ferrie, F. P., & Dudek, G. (2009) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv.2009.5403035 · Cited by 15 · see citing works
Building a Robust System for Multimodal Emotion Recognition
Wagner, J., Lingenfelser, F., & André, E. (2015) · Wiley eBooks · doi:10.1002/9781118910566.ch15 · Cited by 15 · see citing works
Expressive motions recognition and analysis with learning and statistical methods
Ajili, I., Ramezanpanah, Z., Mallem, M., & Didier, J.-Y. (2018) · Multimedia Tools and Applications · doi:10.1007/s11042-018-6893-5 · Cited by 14 · see citing works
Self-aware trader: a new approach to safer trading
Fernández, J. M., Augusto, J. C., Trombino, G., Seepold, R., & Madrid, N. M. (2013) · Middlesex University Research Repository (Middlesex University Of London) · doi:10.3217/jucs-019-15-2292 · Cited by 14 · see citing works
Facial Expression Recognition based on EOG toward Emotion Detection for Human-Robot Interaction
Cruz, A., Garcia, D., Pires, G., & Nunes, U. (2015) · International Conference on Bio-inspired Systems and Signal Processing · doi:10.5220/0005187200310037 · Cited by 14 · see citing works
- Authors
- De Silva, L. C., & Ng, P. C.
- Affiliations
- National University of Singapore (SG)
- Venue
- Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580)
- Publisher
- IEEE Comput. Soc
- Published
- 2002-11-07
- Pages
- 332-335
- ISSN
- 1541-5058 (ISSN-L)
- OpenAlex
- W2115289180
- Semantic Scholar
- b3f14c68fb699ff547d46ff48844b2e2a23823a9
- Cited by
- 196
- References
- 11
- Citations by year
- 2025: 3 · 2024: 1 · 2023: 3 · 2022: 5 · 2021: 7 · 2020: 2 · 2019: 9 · 2018: 9 · 2017: 13 · 2016: 9 · 2015: 13 · 2014: 6 · 2013: 10 · 2012: 11
- FWCI
- 15.39
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Automatic Face and Gesture Recognition (publishedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Physical Sciences › Computer Science › Signal Processing › Speech and Audio Processing
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Keywords
- emotion recognition, bimodal fusion, facial expressions, emotional speech, hidden Markov models, basic emotions, audio-video fusion, multimodal emotion recognition
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
