@inproceedings{oai:naist.repo.nii.ac.jp:00004702,
 author = {Toda, Tomoki and Tokuda, Keiichi},
 month = {Sep},
 note = {This paper describes a novel parameter generation algorithm for the HMM-based speech synthesis. The conventional algorithm generates a trajectory of static features that maximizes an output probability of a parameter sequence consisting of the static and dynamic features from HMMs under an actual constraint between the two features. The generated trajectory is often excessively smoothed due to the statistical processing. Using the over-smoothed trajectory causes the muffled sound. In order to alleviate the over-smoothing effect, we propose the generation algorithm considering not only the output probability used for the conventional method but also that of a global variance (GV) of the generated trajectory. The latter probability works as a penalty for a reduction of the variance of the generated trajectory. A result of a perceptual evaluation demonstrates that the proposed method causes large improvements of the naturalness of synthetic speech.},
 pages = {2801--2804},
 title = {Speech Parameter Generation Algorithm Considering Global Variance for HMM-Based Speech Synthesis},
 year = {2005}
}