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Multiple feed-forward deep neural networks for statistical parametric speech synthesis.

, , , and . INTERSPEECH, page 2242-2246. ISCA, (2015)

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A deep auto-encoder based low-dimensional feature extraction from FFT spectral envelopes for statistical parametric speech synthesis., and . ICASSP, page 5535-5539. IEEE, (2016)An autoregressive recurrent mixture density network for parametric speech synthesis., , and . ICASSP, page 4895-4899. IEEE, (2017)Investigating RNN-based speech enhancement methods for noise-robust Text-to-Speech., , , and . SSW, page 146-152. ISCA, (2016)Investigating Very Deep Highway Networks for Parametric Speech Synthesis., , and . SSW, page 166-171. ISCA, (2016)Characteristics of Polyphonic Music Style and Markov Model of Pitch-Class Intervals., and . MCM, volume 9110 of Lecture Notes in Computer Science, page 109-114. Springer, (2015)Deep Denoising Auto-encoder for Statistical Speech Synthesis., , and . CoRR, (2015)Complex-Valued Restricted Boltzmann Machine for Direct Speech Parameterization from Complex Spectra., , and . CoRR, (2018)STFT spectral loss for training a neural speech waveform model., , , and . CoRR, (2018)Speech Enhancement for a Noise-Robust Text-to-Speech Synthesis System Using Deep Recurrent Neural Networks., , , and . INTERSPEECH, page 352-356. ISCA, (2016)Enhance the Word Vector with Prosodic Information for the Recurrent Neural Network Based TTS System., , and . INTERSPEECH, page 2856-2860. ISCA, (2016)