Statistical parametric speech synthesis based on product of experts
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Heiga Zen | Yoshihiko Nankaku | Keiichi Tokuda | Mark J. F. Gales | H. Zen | M. Gales | K. Tokuda | Yoshihiko Nankaku
[1] Heiga Zen,et al. Estimating Trajectory Hmm Parameters Using Monte Carlo Em With Gibbs Sampler , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.
[2] Heiga Zen,et al. Reformulating the HMM as a Trajectory Model , 2004 .
[3] Heiga Zen,et al. Statistical Parametric Speech Synthesis , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.
[4] Philipp Slusallek,et al. Introduction to real-time ray tracing , 2005, SIGGRAPH Courses.
[5] 全 炳河,et al. Reformulating HMM as a trajectory model by imposing explicit relationships between static and dynamic features , 2006 .
[6] Keiichi Tokuda,et al. Simultaneous modeling of spectrum, pitch and duration in HMM-based speech synthesis , 1999, EUROSPEECH.
[7] Masami Akamine,et al. Multilevel parametric-base F0 model for speech synthesis , 2008, INTERSPEECH.
[8] Geoffrey E. Hinton,et al. Wormholes Improve Contrastive Divergence , 2003, NIPS.
[9] Christopher K. I. Williams. How to Pretend That Correlated Variables Are Independent by Using Difference Observations , 2005, Neural Computation.
[10] Zhizheng Wu,et al. Duration refinement by jointly optimizing state and longer unit likelihood , 2008, INTERSPEECH.
[11] Heiga Zen,et al. The HTS-2008 System: Yet Another Evaluation of the Speaker-Adaptive HMM-based Speech Synthesis System in The 2008 Blizzard Challenge , 2008 .
[12] Max Welling,et al. Product of experts , 2007, Scholarpedia.
[13] Keiichi Tokuda,et al. A Speech Parameter Generation Algorithm Considering Global Variance for HMM-Based Speech Synthesis , 2007, IEICE Trans. Inf. Syst..
[14] Heiga Zen,et al. Reformulating the HMM as a trajectory model by imposing explicit relationships between static and dynamic feature vector sequences , 2007, Comput. Speech Lang..
[15] Radford M. Neal. Probabilistic Inference Using Markov Chain Monte Carlo Methods , 2011 .
[16] Ren-Hua Wang,et al. USTC System for Blizzard Challenge 2006 an Improved HMM-based Speech Synthesis Method , 2006 .
[17] Zhizheng Wu,et al. Improved prosody generation by maximizing joint likelihood of state and longer units , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.
[18] Li-Rong Dai,et al. Multi-Layer F0 Modeling for HMM-Based Speech Synthesis , 2008, 2008 6th International Symposium on Chinese Spoken Language Processing.
[19] Heiga Zen,et al. Details of the Nitech HMM-Based Speech Synthesis System for the Blizzard Challenge 2005 , 2007, IEICE Trans. Inf. Syst..
[20] Geoffrey E. Hinton. Training Products of Experts by Minimizing Contrastive Divergence , 2002, Neural Computation.