Estimating Trajectory Hmm Parameters Using Monte Carlo Em With Gibbs Sampler
暂无分享,去创建一个
Heiga Zen | Yoshihiko Nankaku | Keiichi Tokuda | Tadashi Kitamura | H. Zen | K. Tokuda | Yoshihiko Nankaku | T. Kitamura
[1] Sadaoki Furui,et al. Speaker-independent isolated word recognition using dynamic features of speech spectrum , 1986, IEEE Trans. Acoust. Speech Signal Process..
[2] Mark J. F. Gales,et al. Switching linear dynamical systems for speech recognition , 2003 .
[3] G. C. Wei,et al. A Monte Carlo Implementation of the EM Algorithm and the Poor Man's Data Augmentation Algorithms , 1990 .
[4] Heiga Zen,et al. Trajectory modeling based on HMMs with the explicit relationship between static and dynamic features , 2003, INTERSPEECH.
[5] Heiga Zen,et al. A Viterbi algorithm for a trajectory model derived from HMM with explicit relationship between static and dynamic features , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[6] G. Zweig,et al. Speech recognition using dynamic Bayesian networks , 1998 .
[7] Mari Ostendorf,et al. From HMM's to segment models: a unified view of stochastic modeling for speech recognition , 1996, IEEE Trans. Speech Audio Process..