Design of Intelligent Emotion Recognition Model

  • Kim, Yi-gon (Dept. of Electrical Engineering. Yosu National University)
  • 발행 : 2001.12.01

초록

Voice is one of the most efficient communication media and it includes several kinds of factors about speaker, context emotion and so on. Human emotion is expressed is expressed in the speech, the gesture, the physiological phenomena(the breath, the beating of the pulse, etc). In this paper, the emotion recognition method model using neuro-fuzzy in order to have cognizance of emotion from voice signal is presented and simulated.

키워드

참고문헌

  1. Information Sciences v.101 no.3-4 An Emotion Processing System Based on Fuzzy Interference and Subjective Observations Torao Yanaru;Naruki Shirahama;Kaori Yoshida;Masahiro Nagamatsu
  2. Proceedings of the Fifth International Conference on Neural Information Processing An Emotion Processing System Based on Subjective Observation Torao Yanaru;Naruki Shirahama;Kaori Yoshida;Masahiro Nagamatsu
  3. Digital Processing of affective signals Jennifer Healey;Rosalind Picard
  4. A Mweasurement of Human Vocal Emotion Using Fuzzy Control Tsuyoshi Moriyama;Shinji Ozawa
  5. Proceedings, International Conference on Automatic face and Gesture Recognition Invariant feature for 3-D gesture recogniton L. W. Cambell;D. A. Becker;A. Azarbayjani;A. F. Bobick;A. Pentland
  6. Offline and Online Recognition of Emotion Expression from Physiological Data Elias Vyzas;Rosalind W. Picard
  7. Hybrid Neural Networks and Expert Systems Medsker, L.
  8. Advanced Topics in Artificial Intelligence Model-Based Diagnosis: A Overview Mozetic, I.
  9. Kybernetes v.7 no.3 Fuzzy Relations in a Control Setting M. Braee;D. A. Rutherford
  10. Industrial Applications of Fuzzy Control The Application of a Fuzzy Controller to the Control of a Multi-Degree-Freedom Robot Arm E. M. Scharf;N. J. Mandic;M. Sugeno(ed.)
  11. Fuzzy Sets an Systems v.1 no.1 Analysis of a Fuzzy Logic controller W. J. M. Kicker;E. H. Mamdani
  12. Interal Rep. F/WK2/75 Futher Analysis and Application of Fuzzy Logic Control W. J. M. Kickert
  13. IEEE Trans. on Neural-Network v.11 no.2 Constructive Neural-Network Learning Algorithms for Pattern Classification R. Parekh;J. Yang;V. Honavar
  14. IEEE Antennas and Propagation Mag. v.40 no.5 A Tutorial on Wavelets from an Electrical Engineering Perspective, Part Ⅰ:Discrete Wavelet Techniques T. K. Sarkar;C. Su;R. Adve;M. Salazar-Palma;L. Garcia-Castillo;Rafael R. Boix
  15. IEEE Trans. on Ant. and Prop. v.44 no.9 Diagonal Preconditioners for The EFIE Using a Wavelet Basis F. X. Canning;J. F. School