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This paper proposes a statistical parametric speech synthesis technique based on Gaussian process regression (GPR). The GPR model is designed for directly predicting frame-level acoustic features from corresponding information on frame context that is obtained from linguistic information. The frame context includes the relative position of the current frame within the phone and articulatory information...
We present a nonparametric Bayesian model for completing low-rank, positive semidefinite matrices. Given an N × N matrix with underlying rank r, and noisy measured values and missing values with a symmetric pattern, the proposed Bayesian hierarchical model nonparametrically uncovers the underlying rank from all positive semidefinite matrices, and completes the matrix by approximating the missing values...
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