正在加载图片...
·642· 智能系统学报 第15卷 on Mmultimodal Interaction.Tokyo,Japan,2016: [26]高庆吉,赵志华,徐达,等.语音情感识别研究综述 494-500 智能系统学报,2020,15(1)1-13 [14]ZHANG X,SHEN J,DIN Z U,et al.Multimodal de- GAO Qingji,ZHAO Zhihua,XU Da,et al.Review on pression detection:fusion of electroencephalography and speech emotion recognition research[J].CAAI transac. paralinguistic behaviors using a novel strategy for classi- tions on intelligent systems,2020,15(1):1-13. fier ensemble[J].IEEE journal of biomedical and health [27]JOHNSTON V S.Why we feel:The science of human informatics,,2019,23(6:2265-2275. emotions[M].New York:Perseus publishing,1999 [15]ZONG Y,ZHENG W,HUANG X,et al.Emotion recog- [28]RUSSELL JA.A circumplex model of affect[J].Journ- nition in the wild via sparse transductive transfer linear al of personality and social psychology,1980,39(6): discriminant analysis[J].Journal on multimodal user in- 1161. terfaces,2016,10(2):163-172. [29]MEHRABIAN A.Basic dimensions for a general psy- [16]ZHANG T,ZHENG W,CUI Z,et al.Spatial-temporal chological theory:Implications for personality,social. recurrent neural network for emotion recognition[J]. environmental,and developmental studies[M].Cam- IEEE transactions on systems,man,and cybernetics, bridge:Oelgeschlager Gunn Hain Cambridge,MA. 2019.49(3):839-847 1980. [17]ZHENG W,LIU W,LU Y,et al.Emotionmeter:A mul- [30]ORTONY A,CLORE G L,COLLINS A.The cognitive timodal framework for recognizing human emotions[J]. structure of emotion[J].Contemporary sociology,1988 IEEE transactions on cybernetics,2018,49(3): 18(6):2147-2153 1110-1122 [31]PICARD R W.Affective computing[M].Cambridge: [18]ZHENG W,ZHU J,LU B.Identifying stable patterns MIT press,2000 over time for emotion recognition from EEG[J].IEEE [32]VAN KESTEREN A,OPDEN AKKER R.POEL M,et transactions on affective computing,2019,10(3): al.Simulation of emotions of agents in virtual environ- 417-429 ments using neural networks[J].Learning to behave:in- [19]YAN X.ZHENG W.LIU W,et al.Investigating Gender ternalising knowledge,2000:137-147. differences of brain areas in emotion recognition using [33]PLUTCHIK R.Emotions and life:Perspectives from LSTM neural network[C]//Poceedings of the Internation- psychology,biology,and evolution[M].Washington: al Conference on Neural Information Processing.Guang- American Psychological Association,2003. zhou,China.2017:820-829. [34]IZARD.Human emotions[M].Berlin:Springer Science [20]LI J.QIU S,SHEN Y,et al.Multisource transfer learn- Business Media,2013. ing for cross-subject EEG emotion recognition[J].IEEE [35]ZHUANG N,ZENG Y,YANG K,et al.Investigating transactions on systems,man,and cybernetics,2019, patterns for self-induced emotion recognition from EEG 50(7:1-13. signals[J].Sensors,2018,18(3):841. [21]DU Changde,DU Changying.LI J,et al.Semi-super- [36]IACOVIELLO D.PETRACCA A.SPEZIALETTI M.et vised bayesian deep multi-modal emotion recognition[J]. al.A real-time classification algorithm for EEG-based arXiv preprint arXiv:170407548,2017. BCI driven by self-induced emotions[J].Computer [22]程静.基本情感生理信号的非线性特征提取研究D] methods and programs in biomedicine,2015,122(3): 重庆:西南大学2015. 293-303. CHENG Jing.Research on nonlinear feature extraction [37]RIZZOLATTI G,CRAIGHERO L.The mirror-neuron of basic emotional physiological signals[D].Chongqing: system[J].Annu rev neurosci,2004,27:169-192. Southwest University,2015. [38]LANG P J,BRADLEY MM,CUTHBERT B N.Inter- [23]温万惠.基于生理信号的情感识别方法研究D].重 national affective picture system (IAPS):Technical 庆:西南大学,2010 manual and affective ratings[J].NIMH center for the WEN Wanhui.Research on emotion recognition meth- study of emotion and attention,1997.1:39-58. od based on physiological signals[D].Chongqing, [39]BRADLEY M,LANG P J.The International affective Southwest university,2010. digitized sounds (IADS)[M].Rockville:NIMH center, [24]PICARD R W.Affective computing:challenges[J].In- 1999. ternational journal of human-computer studies,2003, [40]KOELSTRA S.MUHL C.SOLEYMANI M.et al. 59(1-2):55-64. Deap:A database for emotion analysis;using physiolo- [25]EKMAN PE,DAVIDSON R J.The nature of emotion: gical signals[J].IEEE transactions on affective comput- fundamental questions[M].Oxford:Oxford university ing2011,3(1):18-3L. press,1994 [41]SOLEYMANI M,LICHTENAUER J,PUN T,et al.Aon Mmultimodal Interaction. Tokyo, Japan, 2016: 494−500. ZHANG X, SHEN J, DIN Z U, et al. Multimodal de￾pression detection: fusion of electroencephalography and paralinguistic behaviors using a novel strategy for classi￾fier ensemble[J]. IEEE journal of biomedical and health informatics, 2019, 23(6): 2265–2275. [14] ZONG Y, ZHENG W, HUANG X, et al. Emotion recog￾nition in the wild via sparse transductive transfer linear discriminant analysis[J]. Journal on multimodal user in￾terfaces, 2016, 10(2): 163–172. [15] ZHANG T, ZHENG W, CUI Z, et al. Spatial–temporal recurrent neural network for emotion recognition[J]. IEEE transactions on systems, man, and cybernetics, 2019, 49(3): 839–847. [16] ZHENG W, LIU W, LU Y, et al. Emotionmeter: A mul￾timodal framework for recognizing human emotions[J]. IEEE transactions on cybernetics, 2018, 49(3): 1110–1122. [17] ZHENG W, ZHU J, LU B. Identifying stable patterns over time for emotion recognition from EEG[J]. IEEE transactions on affective computing, 2019, 10(3): 417–429. [18] YAN X, ZHENG W, LIU W, et al. Investigating Gender differences of brain areas in emotion recognition using LSTM neural network[C]//Poceedings of the Internation￾al Conference on Neural Information Processing. Guang￾zhou, China, 2017: 820−829. [19] LI J, QIU S, SHEN Y, et al. Multisource transfer learn￾ing for cross-subject EEG emotion recognition[J]. IEEE transactions on systems, man, and cybernetics, 2019, 50(7): 1–13. [20] DU Changde, DU Changying, LI J, et al. Semi-super￾vised bayesian deep multi-modal emotion recognition[J]. arXiv preprint arXiv: 170407548, 2017. [21] 程静. 基本情感生理信号的非线性特征提取研究 [D]. 重庆: 西南大学, 2015. CHENG Jing. Research on nonlinear feature extraction of basic emotional physiological signals[D]. Chongqing: Southwest University, 2015. [22] 温万惠. 基于生理信号的情感识别方法研究 [D]. 重 庆: 西南大学, 2010. WEN Wanhui. Research on emotion recognition meth￾od based on physiological signals[D]. Chongqing, Southwest university, 2010. [23] PICARD R W. Affective computing: challenges[J]. In￾ternational journal of human-computer studies, 2003, 59(1-2): 55–64. [24] EKMAN P E, DAVIDSON R J. The nature of emotion: fundamental questions[M]. Oxford: Oxford university press, 1994. [25] 高庆吉, 赵志华, 徐达, 等. 语音情感识别研究综述 [J]. 智能系统学报, 2020, 15(1): 1–13. GAO Qingji, ZHAO Zhihua, XU Da, et al. Review on speech emotion recognition research[J]. CAAI transac￾tions on intelligent systems, 2020, 15(1): 1–13. [26] JOHNSTON V S. Why we feel: The science of human emotions[M]. New York: Perseus publishing, 1999. [27] RUSSELL J A. A circumplex model of affect[J]. Journ￾al of personality and social psychology, 1980, 39(6): 1161. [28] MEHRABIAN A. Basic dimensions for a general psy￾chological theory: Implications for personality, social, environmental, and developmental studies[M]. Cam￾bridge: Oelgeschlager Gunn & Hain Cambridge, MA, 1980. [29] ORTONY A, CLORE G L, COLLINS A. The cognitive structure of emotion[J]. Contemporary sociology, 1988, 18(6): 2147–2153. [30] PICARD R W. Affective computing[M]. Cambridge: MIT press, 2000. [31] VAN KESTEREN A, OPDEN AKKER R, POEL M, et al. Simulation of emotions of agents in virtual environ￾ments using neural networks[J]. Learning to behave: in￾ternalising knowledge, 2000: 137–147. [32] PLUTCHIK R. Emotions and life: Perspectives from psychology, biology, and evolution[M]. Washington: American Psychological Association, 2003. [33] IZARD. Human emotions[M]. Berlin: Springer Science & Business Media, 2013. [34] ZHUANG N, ZENG Y, YANG K, et al. Investigating patterns for self-induced emotion recognition from EEG signals[J]. Sensors, 2018, 18(3): 841. [35] IACOVIELLO D, PETRACCA A, SPEZIALETTI M, et al. A real-time classification algorithm for EEG-based BCI driven by self-induced emotions[J]. Computer methods and programs in biomedicine, 2015, 122(3): 293–303. [36] RIZZOLATTI G, CRAIGHERO L. The mirror-neuron system[J]. Annu rev neurosci, 2004, 27: 169–192. [37] LANG P J, BRADLEY M M, CUTHBERT B N. Inter￾national affective picture system (IAPS): Technical manual and affective ratings[J]. NIMH center for the study of emotion and attention, 1997, 1: 39–58. [38] BRADLEY M, LANG P J. The International affective digitized sounds (IADS)[M]. Rockville: NIMH center, 1999. [39] KOELSTRA S, MUHL C, SOLEYMANI M, et al. Deap: A database for emotion analysis; using physiolo￾gical signals[J]. IEEE transactions on affective comput￾ing, 2011, 3(1): 18–31. [40] [41] SOLEYMANI M, LICHTENAUER J, PUN T, et al. A ·642· 智 能 系 统 学 报 第 15 卷
<<向上翻页向下翻页>>
©2008-现在 cucdc.com 高等教育资讯网 版权所有