Speech signal-based emotion recognition and its application to entertainment robots

Journal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers,Series A

Volumn 37, Issue 1, 2014, Pages 14-25

  Song, Kai Tai ^a   Han, Meng Ju ^a   Wang, Shih Chieh ^a  

^a NATIONAL CHIAO TUNG UNIVERSITY   (Taiwan)

Author keywords

emotion recognition; human robot interaction; speech signal processing

Indexed keywords

AUDIO SIGNAL PROCESSING; DISCRIMINANT ANALYSIS; HUMAN ROBOT INTERACTION; INTELLIGENT ROBOTS; MAN MACHINE SYSTEMS; SPEECH COMMUNICATION; SUPPORT VECTOR MACHINES;

EMOTION RECOGNITION; END POINT DETECTION; ENTERTAINMENT ROBOTS; HUMAN ROBOT INTERACTION (HRI); LINEAR DISCRIMINANT ANALYSIS; SPEECH SIGNAL PROCESSING; STATISTICAL FEATURES; VOICE SIGNAL PROCESSING;

SPEECH RECOGNITION;

EID: 84892949462     PISSN: 02533839     EISSN: 21587299     Source Type: Journal    
DOI: 10.1080/02533839.2012.751330     Document Type: Article

References (35)

1. Andrian, H., and Song, K.T., 2005. Embedded CMOS imaging system for real-time robotic vision. In: Proceedings of IEEE/RSJ international conference on intelligent robots and systems, 2-6 August 2005 Alberta. Canada: IEEE, 3694-3699.
2. Breazeal, C. 2003. Emotive qualities in lip-synchronized robot speech. Advanced robotics, 17 (2): 97-113.
3. Busso, C., Lee, S., and, Narayanan, S. 2009. Analysis of emotionally salient aspects of fundamental frequency for emotion detection. IEEE transactions on audio, speech, and language processing, 17 (4): 582-596.
4. Chuang, Z.J., and Wu C.H., 2004. Emotion recognition using acoustic features and textual content. In: Proceedings of IEEE international conference on multimedia and expo, 27-30 June 2004 Taipei. Taiwan: IEEE, 53-56.
5. Cristianini, N., and, Shawe-Taylor, J. 2000. An introduction to support vector machines and other kernel-based learning methods, New York, NY: Cambridge University Press.
6. Duda, R.O., and, Hart, P.E. 1973. Pattern classification and scene analysis, New York, NY: Wiley.
7. Gold, B., and, Morgan, N. 2000. Speech and audio signal processing: processing and perception of speech and music, New York, NY: John Wiley.
8. Han, M.J., Hsu, J.H., Song, K.T., and Chang, F.Y. 2007. A new information fusion method for SVM-based robotic audio-visual emotion recognition. In: Proceedings of IEEE international conference on systems, man and cybernetics, 7-10 October 2007 Montreal. Canada: IEEE, 2656-2661.
9. Hyun, K.H., Kim, E.H., and Kwak, Y.K., 2005. Improvement of emotion recognition by Bayesian classifier using non-zero-pitch concept. In: Proceedings of 14th IEEE international workshop on robot and human unteractive communication, 13-15 August 2005 Nashville, TN. USA: IEEE, 312-316.
10. ISCI Lab, intelligent system control integration laboratory, 2011a. Emotional utterance voice clip [online]. Available from: http://isci.cn.nctu. edu.tw/JCIE/VoiceClip/[Accessed 1 August 2012].
11. ISCI Lab, intelligent system control integration laboratory, 2011b. Experimental video clip [online]. Available from: http://isci.cn.nctu.edu.tw/ JCIE/VideoClip/[Accessed 1 August 2012].
12. Jelinek, F. 1999. Statistical methods for speech recognition, Cambridge, MA: MIT Press.
13. Kim, H.C., Kim, D.J., and Bang, S.Y., 2002. Face recognition using LDA mixture model. In: Proceedings of IEEE 16th international conference on pattern recognition, 11-15 August 2002 Quebec. Canada: IEEE, 925-928.
14. Kim, E.H., Hyun, K.H., Kim, S.H., and, Kwak, Y.K. 2009. Improved emotion recognition with a novel speaker-independent feature. IEEE transactions on mechatronics, 14 (3): 317-325.
15. Kwon, O.W., Chan, K., Hao, J., and Lee, T.W. 2003. Emotion recognition by speech signals. In: Proceedings of 8th european conference on speech communication and technology (Eurospeech 03), 1-4 September 2003 Geneva. Switzerland: International Speech Communication Association, 125-128.
16. Li, C., Zhou, Q., Cheng, J., Wu, X., and Xu, Y. 2008. Emotion recognition in a chatting robot. In: Proceedings of 2008 IEEE international conference on automation and logistics, 1-3 September 2008 Qingdao. China: IEEE, 1452-1457.
17. Mika, S., Ratsch, G., Weston, J., Scholkopf, B., and Muller, K.R. 1999. Fisher discriminant analysis with kernels. In: 1999 IEEE international workshop on neural networks for signal processing, 23-25 August 1999 Madison. WI. USA: IEEE, 41-48.
18. Nakajima, H., Nakadai, K., Hasegawa, Y., and, Tsujino, H. 2010. Blind source separation with parameter-free adaptive step-size method for robot audition. IEEE transactions on audio, speech, and language processing, 18 (6): 1476-1485.
19. NEC., 2006. NECs KOTOHANA-Emotion communicator [online]. Available from: http://thefutureofthings.com/pod/1042/necs-kotohana-emotion-communicator.html [Accessed 1 August 2012].
20. Neiberg, D., Elenius, K., and Laskowski, K., 2006. Emotion recognition in spontaneous speech using GMMs. In: Proceedings of 9th ISCA international conference on spoken language processing (INTERSPEECH 2006), 17-21 September 2006 Pittsburgh. PA. USA: International Speech Communication Association, 809-812.
21. Nwe, T.L., Foo, S.W., and, De Silva, L.C. 2003. Speech emotion recognition using hidden Markov models. Speech communication, 41 (4): 603-623.
22. Ogawa, H., and, Watanabe, T. 2001. InterRobot: speech-driven embodied interaction robot. Advanced robotics, 15 (3): 371-377.
23. Pao, T.L., and Chen, Y.T., 2003. Mandarin emotion recognition in speech. In: Proceedings of IEEE workshop on automatic speech recognition and understanding, 30 November-4 December 2003 St. Thomas. Virgin Islands: IEEE, 227-230.
24. Park, J.S., Kim, J.H., and, Oh, Y.H. 2009. Feature vector classification based speech emotion recognition for service robots. IEEE transactions on consumer electronics, 55 (3): 1590-1596.
25. Pololu Robotics and Electronics Inc., 2012. Pololu serial 8-servo controller [online]. Available from: http://www.pololu.com/products/pololu/0727/ [Accessed 1 August 2012].
26. Sato, M., Sugiyama, A., and Ohnaka, S., 2006. Auditory system in a personal robot, PaPeRo. In: Proceedings of IEEE international conference on consumer electronics, 7-11 January 2006 Las Vegas, NV. USA: IEEE, 19-20.
27. Schuller, B., Rigoll, G., and Lang, M., 2004. Speech emotion recognition combining acoustic features and linguistic information in a hybrid support vector machine-Belier network architecture. In: Proceedings of IEEE international conference on acoustics, speech, and signal processing, 17-21 May 2004 Montreal, Quebec. Canada: IEEE, 577-580.
28. Texas Instruments Inc., 2003. TMS320C6416 DSK technical reference [online]. Available from: http://c6000.spectrumdigital.com/dsk6416/V1/docs/ dsk6416-TechRef.pdf [Accessed 1 August 2012].
29. Texas Instruments Inc., 2004. TLV320AIC23B data manual [online]. Available from: http://www.ti.com/lit/ds/symlink/tlv320aic23b.pdf [Accessed 1 August 2012].
30. Valin, J.M., Yamamoto, S., Rouat, J., Michaud, F., Nakadai, Kazuhiro, and, Okuno, H.G. 2007. Robust recognition of simultaneous speech by a mobile robot. IEEE transactions on robotics, 23 (4): 742-752.
31. Vapnik, V. 1995. The nature of statistical learning theory, New York, NY: Springer.
32. Yan, K.M., 2002. Development of a home robot speech recognition system. Thesis (Master). National Chiao Tung University, Hsinchu, Taiwan.
33. Yang, B., and, Lugger, M. 2010. Emotion recognition from speech signals using new harmony features. Signal processing, 90 (5): 1415-1423.
34. You, M, Chen, C., Bu, J., Liu, J., and Tao, J. 2006a. Emotional speech analysis on nonlinear manifold. In: Proceedings of IEEE international conference on pattern recognition, 20-24 August 2006 Hong Kong. China: IEEE, 91-94.
35. You, M, Chen, C., Bu, J., Liu, J., and Tao, J. 2006b. A hierarchical framework for speech emotion recognition. In: Proceedings of IEEE international symposium on industrial electronics, 9-13 July 2006 Montreal, Quebec. Canada: IEEE, 515-519.