@inproceedings{oai:nitech.repo.nii.ac.jp:00003456,
 author = {Wu, Yi-Jian and Tokuda, Keiichi and Qin, Long},
 book = {INTERSPEECH 2009 10th Annual Conference of the International Speech Communication Association},
 month = {Aug},
 note = {application/pdf, Aminimum generation error (MGE) criterion had been proposedfor model training in HMM-based speech synthesis. Inthis paper, we apply the MGE criterion to model adaptation forHMM-based speech synthesis, and introduce an MGE linear regression(MGELR) based model adaptation algorithm, wherethe regression matrices used to transform source models are optimizedso as to minimize the generation errors of adaptationdata. In addition, we incorporate the recent improvements ofMGE criterion into MGELR-based model adaptation, includingstate alignment under MGE criterion and using a log spectraldistortion (LSD) instead of Euclidean distance for spectraldistortion measure. From the experimental results, the adaptationperformance was improved after incorporating these twotechniques, and the formal listening tests showed that the qualityand speaker similarity of synthesized speech after MGELRbasedadaptation were significantly improved over the originalMLLR-based adaptation., Brighton, United KingdomSeptember 6-10, 2009},
 pages = {1787--1790},
 publisher = {International Speech Communication Association},
 title = {An improved minimum generation error based model adaptation for HMM-based speech synthesis},
 year = {2010}
}