@inproceedings{oai:nitech.repo.nii.ac.jp:00003449,
 author = {Wu, Yi Jian and Tokuda, Keiichi and Zen, Heiga and Nankaku, Yoshihiko and 南角, 吉彦},
 book = {Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing},
 month = {Apr},
 note = {application/pdf, Two techniques, including minimum generation error (MGE) criterionfor HMM training, and the parameter generation algorithmconsidering global variance (GV), had been proposed to improve thequality of HMM-based speech synthesis. In this paper, we incorporatethe GV technique into MGE criterion, where an additional generationerror component considering global/local variance (GV/LV)is introduced for generation error definition, and the model parametersare optimized to minimize the new generation error function.From the experimental results, the quality of synthesized speech wasimproved after MGE-GV/LV training, which is similar to the effectivenessof considering GV in parameter generation, however, withoutintroducing any extra computational cost in synthesis process.},
 pages = {4621--4624},
 publisher = {Institute of Electrical and Electronics Engineers},
 title = {Minimum generation error criterion considering global/local variance for HMM-based speech synthesis},
 year = {2008},
 yomi = {ナンカク, ヨシヒコ}
}