MATEC Web of Conferences
Volume 61, 2016The International Seminar on Applied Physics, Optoelectronics and Photonics (APOP 2016)
|Number of page(s)||4|
|Section||Chapter 3 Information Security and Computer Science|
|Published online||28 June 2016|
- L.L. Yu, Z.X. Cai, M.Y. Chens, Study on emotion feature analysis and recognition in speech signal: an overview, J. Circuits and Systems, 12,4 (2007): 76–84.
- Y.H. Yan, Y. Thou, Y.Q. Sun, Feature Extraction Method for Speech Emotion Recognition. China: 2010102729713 (2010).
- X. Mao, L.J. Chen, Speech emotion recognition based on parametric filter and fractal dimension, IEICE T INF SYST, 93,8 (2010): 2324–2326. [CrossRef]
- C.R. Zou, L. Zhao, Speech Emotion Recognition Method Based on Improved Fuzzy Vector Quantization. China: 2008101228062 (2008).
- Y. Attabi, P. Dumouchel, Anchor models for emotion recognition from speech, TAC, 4, 3 (2013): 280–290.
- W.M. Zheng, M.H. Xin, X.L. Wang, A novel speech emotion recognition method via incomplete sparse least square regression, IEEE SIGNAL PROC LET, 21, 5 (2014): 569–572. [CrossRef]
- Q. R. Mao, M. Dong, Z. W. Huang, Learning salient features for speech emotion recognition using convolutional neural networks, IEEE MULTIMEDIA, 16, 8 (2014): 2203–2213. [CrossRef]
- P. Ekman, W. Friesen, Facial action coding system: a technique for the measurement of facial movement. Palo Alto: Consulting Psychologists Press, (1978).
- L.H. Liang, H.Z. Ai, G.Y. Xu, A survey of human face detection, Chinese J. Computers, 25, 5 (2002): 449–458.
- Y. Rahulamathavan, RC. W. Phan, J.A. Chambers, Facial expression recognition in the encrypted domain based on local fisherdiscriminant analysis, TAC, 4, 1 (2013): 83–92.
- W.M. Zheng, Multi-view facial expression recognition based on group sparse reduced-rank regression, TAC, 5, 1 (2014): 71–85.
- P.C. Petrantonakis, L.J. Hadjileontiadis, Emotion recognition from EEG using higher order crossings, IEEE T INF TECHNOL B, 14, 2 (2010): 186–197. [CrossRef]
- S.L. Lin, G.Y. Liu, H.L. Zhang, Application of ACO algorithm to emotion recognition research based on RSP signal, IJCEA, 47, 2 (2011): 169–172.
- H. Zacharatos, H. Gatzoulis, Y.L. Chrysanthou, Automatic emotion recognition based on body movement analysis: a survey, IEEE COMPUT GRAPH, 34, 6 (2014): 35–45. [CrossRef]
- Z. Zeng, M. Pantic, G.I. Roisman, A survey of affect recognition methods: audio, visual, and spontaneous expressions, IEEE T PATTERN ANAL, 31, 1 (2009): 39–58. [CrossRef]
- J. Kim, E. Andre, Emotion recognition based on physiological changes in music listening, IEEE T PATTERN ANAL, 30, 12 (2008): 2067–2083. [CrossRef]
- C.W. Huang, Y. Jin, Q.Y. Wang, Multimodal emotion recognition based on speech and ECG signals, JSEU (NSE), 40, 5 (2010): 895–900.
- C. Busso, Z. Deng, S. Yildirim, Analysis of emotion recognition using facial expressions, speech and multimodal information, ICMI 2004, (2004): 205–211. [CrossRef]
- S. Hoch, F. Althoff, G. Mcglaun, Bimodal fusion of emotional data in an automotive environment, ICASSP 2005, (2005): 1085-1088.
- A. Sayedelahl, R. Araujo, M.S. Kamel, Audio-visual feature-decision level fusion for spontaneous emotion estimation in speech conversations, ICMEW 2013, (2013): 1–6.
- R. Tato, R. Santos, R. Kompe, Emotion space improves emotion recognition, ICSLP 2002, (2002): 2029–2032.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.