Emotional feature extraction method based on the concentration of phoneme influence for human-robot interaction

Advanced Robotics

Volumn 24, Issue 1-2, 2010, Pages 47-67

  Hyun, Kyung Hak ^a   Kim, Eun Ho ^a   Kwak, Yoon Keun ^a  

^a Korea Advanced Institute of Science and Technology (KAIST)   (South Korea)

Author keywords

Emotion recognition; Emotional feature; Feature extraction method; Humanrobot interaction; Phoneme influence

Indexed keywords

AUTOMATIC SPEECH RECOGNITION; CENTER OF GRAVITY; CONCENTRATION OF; EMOTION RECOGNITION; FEATURE EXTRACTION METHODS; FORMANT FREQUENCY; HUMAN ROBOT INTERACTIONS; RESONANCE CHARACTERISTIC; SIGNAL VARIATIONS; SPEECH EMOTION RECOGNITION;

HUMAN COMPUTER INTERACTION; HUMAN ROBOT INTERACTION; MAN MACHINE SYSTEMS; NATURAL FREQUENCIES; SPEECH RECOGNITION;

FEATURE EXTRACTION;

EID: 76649084566     PISSN: 01691864     EISSN: 15685535     Source Type: Journal    
DOI: 10.1163/016918609X12585530487822     Document Type: Article

References (35)

1. C. Breazeal, Function meets style: insights from emotion theory applied to HRI, IEEE Trans. Syst. Man Cybernet. C 34, 187-194 (2004).
2. D. Norman, How might humans interact with robots, in: Proc. DARPA/NSF Workshop on Human-Robot Interaction, San Luis Obispo, Keynote Speech (2001).
3. R. Picard, Affective Computing. MIT Press, Cambridge, MA (1997).
4. P. Rani and N. Sarkar, Emotion-sensitive robots-a new paradigm for human-robot interaction, in: Proc. Int. Conf. on Humanoid Robots, Santa Monica, CA, pp. 149-167 (2004).
5. F. Pransky, AIBO-the No.1 selling service robot, Ind. Robot 28, 24-26 (2001).
6. http://www.irobotics.re.kr/english/index.html
7. P. Rani, C. Liu and N. Sarkar, An empirical study of machine learning techniques for affect recognition in human-robot interaction, Pattern Anal. Applic. 9, 58-69 (2006).
8. C. Breazeal and L. Aryananda, Recognizing affective intent in robot directed speech, Autonomous Robots 12, 83-104 (2002).
9. G. C. Littlewort, M. S. Barlett, J. Chenu, I. Fasel, T. Kanda, H. Ishiguro and J. R. Movellan, Towards social robots: automatic evaluation of human-robot interaction by face detection and expression classification, Adv. Neural Inform. Process. Syst. 16, 1563-1570 (2004).
10. T. P. Spexard, M. Hanheide and G. Sagerer, Human-oriented interaction with an anthropomorphic robot, IEEE Trans. Robotics 23, 852-862 (2007).
11. M. Pantic and L. J. M. Rothkrantz, Toward an affect-sensitive multimodal human-computer interaction, Proc. IEEE 91, 1370-1390 (2003).
12. W. A. Fellenz, J. G. Taylor, R. Cowie, E. Douglas-Cowie, F. Piat, S. Kollias, C. Orovas and B. Apolloni, On emotion recognition of faces and of speech using neural networks, fuzzy logic and the assess system, in: Proc. Int. Joint Conf. on Neural Networks, Como, vol.2, pp. 93-98 (2000).
13. B. S. Kang, C. H. Han, S. T. Lee, D. H. Youn and C. Lee, Speaker dependent emotion recognition using speech signals, in: Proc. Int. Conf. on Spoken Language Processing, Beijing, pp. 383-386 (2000).
14. T. L. Nwe, S. W. Foo and L. C. De Silva, Speech emotion recognition using hidden Markov models, Speech Commun. 41, 603-623 (2003).
15. D. Ververidis and C. Kotropoulos, Emotion speech classification using Gaussian mixture models and the sequential floating forward selection algorithm, in: Proc. Int. Conf. on Multimedia and Expo, Amsterdam, pp. 1500-1503 (2005).
16. O. W. Kwon, K. L. Chan, J. Hao and T. W. Lee, Emotion recognition by speech signals, in: Proc. Eur. Conf. on Speech Communication and Technology (Eurospeech), Geneva, vol.1, pp. 125-128 (2003).
17. R. Banse and K. R. Scherer, Acoustic profiles in vocal emotion expression, J. Personal. Social Psychol. 70, 614-636 (1996).
18. F. Burkhardt and W. F. Sendlmeier, Verification of acoustic correlates of emotional speech using formant synthesis, in: Proc. ISCA Tutorial and Research Workshop on Speech and Emotion, Newcastle, pp. 151-156 (2000).
19. B. S. Atal, Effectiveness of linear prediction characteristics of the speech wave for automatic speaker identification and verification, J. Acoust. Soc. Am. 55, 1304-1312 (1974).
20. S. B. Davis and P. Mermelstei, Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences, IEEE Trans. Acoust. Speech Signal Process. 28, 357-366 (1980).
21. C. M. Lee, S. Yildirim, M. Bulut, A. Kazemzadeh, C. Busso, Z. Deng, S. Lee and S. Narayanan, Emotion recognition based on phoneme classes, in: Proc. Int. Conf. on Spoken Language Processing, Jeju, pp. 889-892 (2004).
22. L. Leinonen and T. Hiltunen, Expression of emotional motivational connotations with a one-word utterance, J. Acoust. Soc. Am. 102, 1853-1863 (1997).
23. J. Kittler, M. Hatef, R. P. W. Duin and J. Matas, On combining classifiers, IEEE Trans. Pattern Anal. Mach. Intelli. 20, 226-239 (1998).
24. J. E. Higgins, T. J. Dodd and R. I. Damper, Application of multiple classifier techniques to subband speaker identification with an HMM/ANN system, Lecture Notes Comp. Sci. 2096, 369-377 (2001).
25. G. J. Borden, K. S. Harris and L. J. Raphael, Speech Science Primer: Physiology, Acoustics, and Perception, 3rd edn. Williams & Wilkins, Baltimore, MD (1994).
26. R. J. J. H. van Son and L. C. W. Pols, An acoustic description of consonant reduction, Speech Commun. 28, 125-140 (1999).
27. T. F. Quatieri, Discrete-Time Speech Signal Processing: Principles and Practice. Prentice-Hall, Upper Saddle River, NJ (2002).
28. T. Kim, Y. Kang and H. Ko, Achieving real-time lip synch via SVM-based phoneme classification and lip shape refinement, in: Proc. IEEE Int. Conf. on Multimodal Interfaces, Pittsburgh, PA, pp. 299-304 (2002).
29. G. E. Peterson and H. L. Barney, Control method used in a study of the vowels, J. Acoust. Soc. Am. 24, 175-184 (1952).
30. E. H. Kim, K. H. Hyun and Y. K. Kwak, Improvement of emotion recognition from voice by separating of obstruents, in: Proc. 15th IEEE Int. Symp. on Robot and Human Interactive Communication (RO-MAN), Hatfield, pp. 564-568 (2006).
31. X. Sun, Pitch determination and voice quality analysis using subharmonic-to-harmonic ratio, in: Proc. Int. Conf. on Acoustics, Speech, and Signal Processing, Orlando, FL, pp. 333-336 (2002).
32. V. Franc, http://cmp.felk.cvut.cz/cmp/software/stprtool/index.html (2007).
33. B. S. Kang, C.-H. Han, C. Lee and D.-H. Youn, Recognizing six emotional states using speech signals, in: Proc. Spring Conf. of KOSES & International Sensibility Ergonomics Symp., Daejeon, pp. 366-369 (2000).
34. T. M. Mitchell, Machine Learning. McGraw-Hill, New York, NY (1997).
35. M. Nishida and T. Kawahara, Speaker model selection based on the Bayesian information criterion applied to unsupervised speaker indexing, IEEE Trans. Speech Audio Process. 13, 583-592 (2004).