HMM based synthesis has attracted great interest due to its compact and flexible modelling of spectral and prosodic parameters. In this approach, short term spectra, fundamental ...
Kai Yu, Tomoki Toda, Milica Gasic, Simon Keizer, F...
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
In this paper, a novel two-tier Bayesian based method is proposed for hair segmentation. In the first tier, we construct a Bayesian model by integrating hair occurrence prior prob...
Dan Wang, Shiguang Shan, Wei Zeng, Hongming Zhang,...
We have previously proposed a trajectory model which is based on a mixture density network (MDN) trained with target variables augmented with dynamic features together with an algo...
We propose novel approaches for optimizing the detection performance in spoken language recognition. Two objective functions are designed to directly relate model parameters to tw...