Emotion recognition and adaptation in spoken dialogue systems

International Journal of Speech Technology

Volumn 13, Issue 1, 2010, Pages 49-60

  Pittermann, Johannes ^a   Pittermann, Angela ^a   Minker, Wolfgang ^a  

^a UNIVERSITY OF ULM   (Germany)

Author keywords

Adaptive dialogue management; Combined speech and emotion recognition; Evaluation; Feature extraction; ROVER

Indexed keywords

ADAPTIVE DIALOGUE MANAGEMENT; AUTOMATIC SPEECH RECOGNITION; DIALOGUE MANAGEMENT; DIALOGUE MODELS; EMOTION MODELS; EMOTION RECOGNITION; EMOTIONAL STATE; EVALUATION; EXPERIMENTAL SETUP; HUMAN COMPUTER INTERFACES; POSTPROCESSING ALGORITHMS; SPOKEN DIALOGUE SYSTEM; STOCHASTIC APPROACH; TEXTUAL CONTENT; WEIGHTING FACTORS;

FEATURE EXTRACTION; SPEECH PROCESSING; STOCHASTIC MODELS; USER INTERFACES;

SPEECH RECOGNITION;

EID: 77950021520     PISSN: 13812416     EISSN: 15728110     Source Type: Journal    
DOI: 10.1007/s10772-010-9068-y     Document Type: Article

References (24)

1. André, E., Rehm, M., Minker, W., & Bühler, D. (2004). Endowing spoken language dialogue systems with emotional intelligence. In Tutorial and research workshop affective dialogue systems (pp. 178-187), Irsee, Germany, June 2004.
2. Batliner, A., Hacker, C., Steidl, S., Nöth, E., & Haas, J. (2004). User states, user strategies, and system performance: how to match the one with the other. In International conference on language resources and evaluation (LREC) (pp. 171-174), Lisbon, Portugal.
3. P. Boersma 2001 Praat, a system for doing phonetics by computer Glot International 5 9/10 341 345
4. Bui, T. H., Zwiers, J., Poel, M., & Nijholt, A. (2006). Toward affective dialogue modeling using partially observable Markov decision processes. In Proceedings of workshop emotion and computing, 29th annual German conference on artificial intelligence, Bremen, Germany, June 2006.
5. Burkhardt, F., Ajmera, J., Englert, R., Stegmann, J., & Burleson, W. (2006). Detecting anger in automated voice portal dialogs. In International conference on speech and language processing (ICSLP) (pp. 1053-1056), Pittsburgh, USA, September 2006.
6. Burkhardt, F., Paeschke, A., Rolfes, M., Sendlmeier, W.F., & Weiss, B. (2005). A database of German emotional speech. In European conference on speech and language processing (EUROSPEECH) (pp. 1517-1520), Lisbon, Portugal, September 2005.
7. Cowie, R., & Cornelius, R.R. (2003). Describing the emotional states that are expressed in speech. In Speech communication (Vol. 40, pp. 5-32).
8. Fiscus, J.G. (1997). A post-processing system to yield reduced word error rates: recogniser output voting error reduction (ROVER). In Proceedings of the IEEE workshop on automatic speech recognition and understanding (pp. 347-352), Santa Barbara, USA.
9. Kwon, O.-W., Chan, K., Hao, J., & Lee, T.-W. (2003). Emotion recognition by speech signals. In European conference on speech and language processing (EUROSPEECH) (pp. 125-128), Geneva, Switzerland.
10. Larson, J.A. (2001). VoiceXML 2.0 and the W3C speech interface framework. In IEEE workshop on automatic speech recognition and understanding (ASRU) (pp. 5-8).
11. E. Levin R. Pieraccini W. Eckert 2000 A stochastic model of human machine interaction for learning dialog strategies IEEE Transactions on Speech and Audio Processing 8 1 11 23 10.1109/89.817450 (Pubitemid 30540744)
12. D.J. Litman S. Pan 2002 Designing and evaluating an adaptive spoken dialogue system User Modeling and User-Adapted Interaction 12 111 137 1030.68759 10.1023/A:1015036910358 (Pubitemid 34491077)
13. Luengo, I., Navas, E., Hernáez, I., & Sánchez, J. (2005). Automatic emotion recognition using prosodic parameters. In International conference on speech and language processing (ICSLP) (pp. 493-496), Lisbon, Portugal, September 2005.
14. McTear, M.F. (2004). Spoken dialogue technology-toward the conversational user interface. Berlin: Springer.
15. Neiberg, D., Elenius, K., & Laskowski, K. (2006). Emotion recognition in spontaneous speech using GMMs. In International conference on speech and language processing (ICSLP) (pp. 809-812), Pittsburgh, USA, September 2006.
16. Pittermann, A., & Pittermann, J. (2006). Getting bored with HTK? Using HMMs for emotion recognition. In 8th international conference on signal processing (ICSP) (Vol. 1, pp. 704-707), Guilin, China, November 2006.
17. Pittermann, J., & Pittermann, A. (2007). A data-oriented approach to integrate emotions in adaptive dialogue management. In International conference on intelligent user interfaces (IUI) (pp. 270-273), Honolulu, USA, January 2007.
18. Pittermann, J., Pittermann, A., Meng, H., & Minker, W. (2007). Towards an emotion-sensitive spoken dialogue system-classification and dialogue modeling. In 3rd IET international conference on intelligent environments, Ulm, Germany, September 2007.
19. J. Pittermann A. Pittermann W. Minker 2007 Design and implementation of adaptive dialogue strategies for speech-based interfaces Journal of Ubiquitous Computing and Intelligence 1 2 145 152 10.1166/juci.2007.208
20. Reeves, B., & Nass, C. (1996). The media equation: how people treat computers, television, and new media like real people and places. Cambridge: Cambridge University Press.
21. Schmitt, A., Hank, C., & Liscombe, J. (2008). Detecting problematic calls wit automated agents. In 4th IEEE tutorial an research workshop on perception and interactive technologies for speech-based systems, Irsee, Germany.
22. Vogt, T., & André, E. (2006). Improving automatic emotion recognition from speech via gender differentiation. In International conference on language resources and evaluation (LREC) (pp. 1123-1126), Genova, Italy, May 2006.
23. Williams, J.D., Poupart, P., & Young, S. (2005). Partially observable Markov decision processes with continuous observations for dialogue management. In Proceedings of the 6th SIGdial workshop on discourse and dialogue, Lisbon, Portugal.
24. Young, S. (1994). The HTK hidden Markov model toolkit: design and philosophy (Tech. Rep. CUED/F-INFENG/TR152). Cambridge University Engineering Department, UK.