IMPROVEMENT OF MAP-VFS ADAPTATION PERFORMANCE BY FUZZY CONTROL

Ing-Jr Ding

References

  1. [1] J.L. Gauvain & C.H. Lee, Maximum a posteriori estimation for multivariate gaussian mixture observations of Markov chains, IEEE Transactions on Speech and Audio Processing, 2(2), 1994, 291–298.
  2. [2] K. Shinoda & C.-H. Lee, Structural MAP speaker adaptation using hierarchical priors, Proc. IEEE Workshop on Automatic Speech Recognition and Understanding, Santa Barbara, CA, USA, 1997, 381–388.
  3. [3] K. Ohkura, M. Sugiyama, & S. Sagayama, Speaker adaptation based on transfer vector field smoothing with continuous mixture density HMMs, Proc. Int. Conf. on Spoken Language Processing, Banff, Canada, 1992, 369–372. 122
  4. [4] H. Hattori & S. Sagayama, Vector field smoothing principle for speaker adaptation, Proc. Int. Conf. on Spoken Language Processing, Banff, Canada, 1992, 381–384.
  5. [5] J. Ishii, M. Tonomura, & S. Matsunaga, Speaker adaptation using tree structured shared-state HMMs, Proc. Int. Conf. on Spoken Language Processing, Philadelphia, PA, USA, 1996, 1149–1152.
  6. [6] J.-I. Takahashi & S. Sagayama, Vector-field-smoothed Bayesian learning for fast and incremental speaker/telephone-channel adaptation, Computer Speech and Language, 11, 1997, 127–146.
  7. [7] C.J. Leggetter & P.C. Woodland, Maximum likelihood linear regression for speaker adaptation of continuous density hidden Markov models, Computer Speech and Language, 9, 1995, 171–185.
  8. [8] J.T. Chien & H.C. Wang, Telephone speech recognition based on Bayesian adaptation of hidden Markov models, Speech Communication, 22, 1997, 369–384.
  9. [9] C. Chesta, O. Siohan, & C.H. Lee, Maximum a posteriori linear regression for hidden Markov model adaptation, Proc. European Conf. on Speech Communication and Technology, Budapest, Hungary, 1999, 211–214.
  10. [10] O. Siohan, T.A. Myrvoll, & C.-H. Lee, Structural maximum a posteriori linear regression for fast HMM adaptation, Proc. ISCA Workshop on Automatic Speech Recognition, 2000, 120–127.
  11. [11] R. Kuhn, J.-C. Junqua, P. Nguyen, & N. Niedzielski, Rapid speaker adaptation in eigenvoice space, IEEE Transactions on Speech and Audio Processing, 8(6), 2000, 695–707.
  12. [12] K.T. Chen, W.W. Liau, H.M. Wang, & L.S. Lee, Fast speaker adaptation using eigenspace-based maximum likelihood linear regression, Proc. Int. Conf. on Spoken Language Processing, Beijing, China, 2000, 742–745.
  13. [13] B. Mak, J.T. Kwok, & S. Ho, Kernel eigenvoice speaker adaptation, IEEE Transactions on Speech and Audio Processing, 13(5), 2005, 984–992.
  14. [14] B. Zhou & J. Hansen, Rapid discriminative acoustic model based on eigenspace mapping for fast speaker adaptation, IEEE Transactions on Speech and Audio Processing, 13(4), 2005, 554–564.
  15. [15] B. Mak, R. Hsiao, S. Ho, & J.T. Kwok, Embedded kernel eigenvoice speaker adaptation and its implication to reference speaker weighting, IEEE Transactions on Audio, Speech, and Language Processing, 14(4), 2006, 1267–1280.
  16. [16] B. Mak & R. Hsiao, Kernel eigenspace-based MLLR adaptation, IEEE Transactions on Audio, Speech, and Language Processing, 15(3), 2007, 784–795.
  17. [17] R. Yager & D. Filev, Essentials of fuzzy modeling and control (New York: Wiley, 1994).
  18. [18] T. Takagi & M. Sugeno, Fuzzy identification of systems and its applications to modeling and control, IEEE Transactions on Systems, Man and Cybernetics, 15, 1985, 116–132.
  19. [19] J. Yen, R. Langari, & L.A. Zadeh (Eds.), Industrial applications of fuzzy logic and intelligent systems (New York: IEEE Press, 1995).
  20. [20] S. Kermiche, M.L. Saidi, H.A. Abbassi, & H. Ghodbane, Takagi–Sugeno based controller for mobile robot navigation, Journal of Applied Science, 6(8), 2006, 1838–1844.
  21. [21] C.T. Lin, H.W. Nein, & W.F. Lin, Speaker adaptation of fuzzyperceptron-based speech recognition, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 7(1), 1999, 1–30.
  22. [22] P. Melin, J. Urias, D. Solano, M. Soto, M. Lopez, & O. Castillo, Voice recognition with neural networks, fuzzy logic and genetic algorithms, Engineering Letters, 13(2), 2006, 108–116.
  23. [23] Y.T. Juang, K.C. Huang, & I.J. Ding, Speaker adaptation based on MAP estimation using fuzzy controller, Pattern Recognition Letters, 24(15), 2003, 2807–2813.
  24. [24] C.H. Lee, C.H. Lin, & B.H. Juang, A study on speaker adaptation of the parameters of continuous density hidden Markov models, IEEE Transactions on Acoustics, Speech and Signal Processing, 39(4), 1991, 806–814.
  25. [25] B.H. Juang & L.R. Rabiner, The segmental k-means algorithm for estimating parameters of hidden Markov models, IEEE Transactions on Signal Processing, 38(9), 1990, 1639–1641.
  26. [26] H.C. Wang, F. Seide, C.Y. Tseng, & L.S. Lee, MAT-2000 – Design, collection, and validation of a Mandarin 2000-speaker telephone speech database, Proc. Int. Conf. on Spoken Language Processing, Beijing, China, 2000, 460–463.
  27. [27] C.H. Lin, C.H. Wu, P.Y. Ting, & H.M. Wang, Frameworks for recognition of Mandarin syllables with tones using sub-syllabic units, Speech Communication, 18(2), 1996, 175–190.

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