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Speaker identification using Gaussian mixture models based on multi-space probability distribution.

, , , , , and . ICASSP, page 433-436. IEEE, (2001)

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State Duration Modeling for HMM-Based Speech Synthesis., , , , , and . IEICE Trans. Inf. Syst., 90-D (3): 692-693 (2007)Applying Complex-Valued Neural Networks to Acoustic Modeling for Speech Recognition., , and . APSIPA, page 1725-1731. IEEE, (2018)Speech Synthesis with Various Emotional Expressions and Speaking Styles by Style Interpolation and Morphing, , , and . IEICE Transactions on Information and Systems, E88-D (11): 2484-2491 (November 2005)A context clustering technique for average voice models, , , , and . IEICE Transactions on Information and Systems, E86-D (3): 534-542 (March 2003)A hidden semi-Markov model-based speech synthesis system, , , , and . IEICE Transactions on Information and Systems, E90-D (5): 825-834 (May 2007)Speaker adaptation of pitch and spectrum for HMM-based speech synthesis., , , and . Syst. Comput. Jpn., 35 (11): 59-68 (2004)A duration modeling technique with incremental speech rate normalization., , and . INTERSPEECH, page 2962-2965. ISCA, (2010)A style control technique for HMM-based speech synthesis., , and . INTERSPEECH, page 1437-1440. ISCA, (2004)Investigation of State Duration Model based on Gamma distribution for HMM-based Speech Synthesis, , , , and . IEICE Technical Report, 101 (352): 57-62 (October 2001)A study on state duration modeling using lognormal distribution for HMM-based speech synthesis, , and . Proceedings of the 2004 Spring Meeting of the Acoustical Society of Japan (ASJ), 1-7-7, page 225-226. (2004)