Combining multiple high quality corpora for improving HMM-TTS
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Heiga Zen | Mark J. F. Gales | Kate Knill | Masami Akamine | K. K. Chin | Vincent Wan | Javier Latorre | Langzhou Chen | H. Zen | M. Gales | V. Wan | K. Knill | Langzhou Chen | Javier Latorre | M. Akamine
[1] Mark J. F. Gales,et al. Adaptation of precision matrix models on large vocabulary continuous speech recognition , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..
[2] Keiichi Tokuda,et al. Spectral conversion based on maximum likelihood estimation considering global variance of converted parameter , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..
[3] Sabine Buchholz,et al. Crowdsourcing Preference Tests, and How to Detect Cheating , 2011, INTERSPEECH.
[4] Mark J. F. Gales,et al. Speech factorization for HMM-TTS based on cluster adaptive training , 2012, INTERSPEECH.
[5] Takao Kobayashi,et al. Analysis of Speaker Adaptation Algorithms for HMM-Based Speech Synthesis and a Constrained SMAPLR Adaptation Algorithm , 2009, IEEE Transactions on Audio, Speech, and Language Processing.
[6] Mark J. F. Gales. Cluster adaptive training of hidden Markov models , 2000, IEEE Trans. Speech Audio Process..
[7] Heiga Zen,et al. Statistical Parametric Speech Synthesis Based on Speaker and Language Factorization , 2012, IEEE Transactions on Audio, Speech, and Language Processing.
[8] Cenk Demiroglu,et al. HMM-based text to speech system with speaker interpolation , 2011, 2011 IEEE 19th Signal Processing and Communications Applications Conference (SIU).
[9] Mark J. F. Gales,et al. Exploring Rich Expressive Information from Audiobook Data Using Cluster Adaptive Training , 2012, INTERSPEECH.