Cultural dependency analysis for understanding speech emotion

Expert Systems with Applications

Volumn 39, Issue 5, 2012, Pages 5115-5133

  Kamaruddin, Norhaslinda ^a   Wahab, Abdul ^b   Quek, Chai ^c  

^a UNIVERSITI TEKNOLOGI MARA   (Malaysia)

^b INTERNATIONAL ISLAMIC UNIVERSITY MALAYSIA   (Malaysia)

^c NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Affective space model; Fuzzy Neural Network; Inter cultural and Intra cultural Assessment; Mel Frequency Cepstral Co efficient; Neural Network; Speech Emotion Recognition System

Indexed keywords

CEPSTRAL; FUZZY-NEURAL; INTER-CULTURAL AND INTRA-CULTURAL ASSESSMENT; SPACE MODELS; SPEECH EMOTION RECOGNITION SYSTEM;

BEHAVIORAL RESEARCH; COMMUNICATION SYSTEMS; EXPERIMENTS; FUZZY INFERENCE; FUZZY NEURAL NETWORKS; HUMAN ROBOT INTERACTION; INTELLIGENT VEHICLE HIGHWAY SYSTEMS; NETWORK LAYERS; NEURAL NETWORKS; SPEECH COMMUNICATION;

SPEECH RECOGNITION;

EID: 84855898663     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2011.11.028     Document Type: Article

References (54)

1. K.K. Ang, and C. Quek RSPOP: Rough set-based pseudo outer-product fuzzy rule identification algorithm Neural Computation 17 1 2005 205 243
2. R.V. Bezooijen, S.A. Otto, and T.A. Heenan Recognition of vocal expression of emotion: A three-nation study to identify universal characteristics Journal of Cross-cultural Psychology 14 4 1983 387 406
3. C. Bishop Neural networks for pattern recognition 1997 Clarendon Press Oxford
4. Burkhardt, F.; Paeschke, A.; Rolfes, M.; Sendlmeier, W.; Weiss, B. (2005). A database of german emotional speech. In Proceeding of INTERSPEECH'05 (pp. 1517-1520), Lisbon, Portugal.
5. Z. Callejas, and R. Lopez-Cozar Influence of contextual information in emotion annotation for spoken dialogue systems Speech Communication 50 5 2008 416 433
6. E.Y. Cheu, C. Quek, and S.K. Ng ARPOP: An appetitive reward-based pseudo-outer-product neural fuzzy inference system inspired from the operant conditioning of feeding behaviour in Aplysia IEEE Transactions on Neural Networks 2010
7. S.L. Chiu Fuzzy model identification based on cluster estimation Journal of Intelligent and Fuzzy Systems 2 3 1994 267 278
8. R.R. Cornelius The science of emotion: Research and tradition in the psychology of emotion 1996 Prentice-Hall Upper Saddle River, NJ
9. R. Cowie, and R.R. Cornelius Describing the emotional states that are expressed in speech Speech Communication 40 1-2 2003 5 32
10. A.R. Damasio Descartes' error: Emotion reason, and the human, brain 1994 Putman London, UK
11. S.B. Davis, and P. Mermelstein Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences IEEE Transaction on Acoustic, Speech and Signal Processing 28 4 1980 357 366
12. J-M. Dewaele The emotional weight of 'I love you' in multilingual's languages Journal of Pragmatics 40 10 2008 1753 1780
13. H.A. Elfenbein, and N. Ambady On the universality and cultural specificity of emotion recognition: A meta-analysis Psychological Bulletin 128 2 2002 203 235
14. N.H. Frijda Emotions, cognitive structures and action tendency Cognition and Emotion 1 1986 115 143
15. Ganchev, T.; Fakotakis, N.; Kokkinakis, G. (2005). Comparative evaluation of various MFCC implementations on the speaker verification task. In Proceeding of the 10th international conference on speech and computer (SPECOM 2005) (Vol. 1, pp. 191-194).
16. H.L. Goh, J.H. Lim, and C. Quek Fuzzy associative conjuncted maps networks IEEE Transactions on Neural Networks 20 8 2009 1302 1319
17. M. Grimm, K. Kroschel, E. Mower, and S. Narayanan Primitives-based evaluation and estimation of emotion in speech Speech Communication 49 10-11 2007 787 800
18. J.S.R. Jang ANFIS: Adaptive network-based fuzzy inference system IEEE Transactions on Systems, Man and Cybernetics 23 3 1993 665 685
19. P.N. Juslin, and P. Laukka Communication of emotions in vocal expression and music performance: Different channels, same code? Psychological Bulletin 129 5 2003 770 814
20. Kamaruddin, N.; Wahab, A. (2008). Speaker independent emotion recognition system - SIERS. In Proceeding of the 2008 international conference on artificial intelligence (ICAI'08) (pp. 10-15), Las Vegas, Nevada, USA.
21. Kamaruddin, N.; Wahab, A. (2009a). A CMAC for speech emotion profiling. In Proceeding of the 10th annual conference of the international speech communication association (INTERSPEECH 2009) (pp. 1991-1994), Brighton, England, United Kingdom.
22. Kamaruddin, N.; Wahab, A. (2009b). Speech emotion profiling for inter and intra cultural assessment. In Proceeding of the 18th international conference on software engineering and data engineering (SEDE 2009) (pp. 275-280), Las Vegas, Nevada, USA.
23. Kamaruddin, N.; Wahab, A. (2010). Cultural influence on speech emotion identification. In Proceeding of the 25th international conference on computer and its application (CATA 2010) (pp. 264-269), Honolulu, Hawaii, USA.
24. N. Kamaruddin, and A. Wahab Features extraction for speech emotion Journal of Computational Methods in Science and Engineering 9 S1 2009 S1 S12
25. P.J. Lang The emotion probe: Studies of motivation and attention American Psychologist 50 5 1995 372 385
26. F. Liu, C. Quek, and G.S. Ng A novel generic Hebbian ordering-based fuzzy rule base reduction approach to Mamdani neuro-fuzzy system Neural Computation 19 6 2007 1656 1680
27. E.H. Mamdani Application of fuzzy logic to approximate reasoning using linguistic systems IEEE Transaction on Computing C-26 1977 1182 1191
28. M.N. Nguyen, D. Shi, and C. Quek FCMAC-BYY: Fuzzy CMAC using Bayesian Ying-Yang learning IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics 36 5 2006 1180 1190
29. J. Nicholson, K. Takahashi, and R. Nakatsu Emotion recognition in speech using neural networks Neural Computing and Applications 9 4 2000 290 296
30. T.L. Nwe, S.W. Foo, and L.C. De Silva Speech emotion recognition using hidden Markov models Speech Communication 41 4 2003 603 623
31. M.D. Pell, L. Monetta, S. Paulmann, and S.A. Kotz Recognizing emotions in foreign language Journal of Nonverbal Behavior 33 2 2009 107 120
32. M.D. Pell, S. Paulmann, C. Dara, A. Alasseri, and S.A. Kotz Factors in the recognition of vocally expressed emotion: A comparison of four languages Journal of Phonetics 37 2009 417 435
33. K.H. Quah, and C. Quek MCES: A novel Monte Carlo evaluative selection approach for objective feature selections IEEE Transactions on Neural Networks 18 2 2007 431 448
34. C. Quek, and A. Singh POP-Yager: A novel self-organizing fuzzy neural network based on the Yager inference Expert Systems with Applications 29 1 2005 229 242
35. C. Quek, and R.W. Zhou Structure and learning algorithms of a nonsingleton input fuzzy neural network based on the approximate analogical reasoning schema Fuzzy Sets and Systems 157 13 2006 1814 1831
36. L.R. Rabiner, and B.H. Juang Fundamentals of speech emotion recognition 1993 Prentice-Hall Englewood Cliffs, NJ
37. K.R. Scherer Vocal affect expression: A review and a model for future research Psychological Bulletin 99 1986 143 165
38. K.R. Scherer Vocal communication of emotion: A review of research paradigm Speech Communication 40 1-2 2003 227 256
39. K.R. Scherer, R. Banse, and H.G. Wallbott Emotion inferences from vocal expression correlate across languages and cultures Journal of Cross-Cultural Psychology 32 1 2001 76 92
40. H. Schlosberg Three dimensions of emotion Psychological Review 61 2 1954 81 88
41. A. Singh, C. Quek, and S.-Y. Cho DCT-Yager FNN: A novel Yager-based fuzzy neural network with the discrete clustering technique IEEE Transactions on Neural Networks 19 4 2008 625 644
42. M.D. Skowronski, and J.G. Harris Exploiting independent filter bandwidth of human factor cepstral coefficient in automatic speech recognition Journal of Acoustical Society of America 116 3 2004 1774 1780
43. Slaney, M. (1998). Auditory Toolbox, Version 2. Technical report #1998-010. Interval Research Corporation. Available at: .
44. J. Tan, and C. Quek BCM theory of meta-plasticity for online self-reorganizing fuzzy-associative learning IEEE Transactions on Neural Networks 21 6 2010 985 1003
45. Tung, W. L.; Quek, C. (2002b). DIC: A novel discrete incremental clustering technique for the derivation of fuzzy membership functions. In PRICAI 2002: Trends in artificial intelligence. Lecture notes in computer science (Vol. 2417, pp. 485-491).
46. S.W. Tung, C. Quek, and C.T. Guan SaFIN: A self-adjusting fuzzy inference networks IEEE Transactions on Neural Networks 2011
47. W.L. Tung, and C. Quek GenSoFNN: A generic self-organizing fuzzy neural network IEEE Transaction of Neural Networks 13 2002 1075 1086
48. W.L. Tung, and C. Quek eFSM - A novel online neural-fuzzy semantic memory model IEEE Transactions on Neural Networks 21 1 2010 136 157
49. Ververidis, D.; Kotropoulus, C. (2003). A state of the art review on emotional speech databases. In Proceeding of 1st Richmedia conference (pp. 109-119), Lausanne, Switzerland.
50. D. Ververidis, and C. Kotropoulos Emotional speech recognition: Resources, features and methods Speech Communication 48 9 2006 1162 1181
51. D. Wang, C. Quek, and G.S. Ng Novel self-organizing Takagi Sugeno Kang fuzzy neural networks based on ART-like clustering Neural Processing Letter 20 1 2004 39 51
52. K.C. Wong, S.Y. Cho, and C. Quek R-POPTVR: A novel reinforcement-based POPTVR fuzzy neural network for pattern classification IEEE Transactions on Neutral Networks 20 11 2009 1740 1755
53. R. Yager, and D. Filev Generation of fuzzy rules by mountain clustering Journal of Intelligent Fuzzy System 2 1994 209 219
54. Young, S. J.; Odell, J.; Ollason, D.; Valtchev, V.; Woodland, P. (1995). The HTK book, Version. 2.1. UK: Department of Engineering, Cambridge University.