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Details of the Nitech HMM-Based Speech Synthesis System for the Blizzard Challenge 2005, , , and . IEICE Transactions on Information and Systems, E90-D (1): 325-333 (January 2007)Hidden Semi-Markov Model Based Speech Recognition System using Weighted Finite-State Transducer., , , , and . ICASSP (1), page 33-36. IEEE, (2006)Directly modeling speech waveforms by neural networks for statistical parametric speech synthesis., and . ICASSP, page 4215-4219. IEEE, (2015)On the use of kernel PCA for feature extraction in speech recognition., , , , , and . INTERSPEECH, page 2625-2628. ISCA, (2003)Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling, , , , , , , , , and 81 other author(s). (2019)cite arxiv:1902.08295.CVSS Corpus and Massively Multilingual Speech-to-Speech Translation., , , and . LREC, page 6691-6703. European Language Resources Association, (2022)Generating Diverse and Natural Text-to-Speech Samples Using a Quantized Fine-Grained VAE and Autoregressive Prosody Prior., , , , , , , and . ICASSP, page 6699-6703. IEEE, (2020)Fully-Hierarchical Fine-Grained Prosody Modeling For Interpretable Speech Synthesis., , , , , and . ICASSP, page 6264-6268. IEEE, (2020)An overview of nitech HMM-based speech synthesis system for blizzard challenge 2005., and . INTERSPEECH, page 93-96. ISCA, (2005)Tying covariance matrices to reduce the footprint of HMM-based speech synthesis systems., , , , and . INTERSPEECH, page 1759-1762. ISCA, (2009)