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Speech parameter generation considering global variance (GV generation) is widely acknowledged to dramatically improve the quality of synthetic speech generated by HMM-based systems. However it is slower and has higher latency than the standard speech parameter generation algorithm. In addition it is known to produce artifacts, though existing approaches to prevent artifacts are effective. We present a simple new theoretical analysis of speech parameter generation considering global variancedoi:10.1109/icassp.2013.6639196 dblp:conf/icassp/ShannonB13 fatcat:kccwzzmfajctxa6qf5wdeucg44