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Constructing a Deep Neural Network Based Spectral Model for Statistical Speech Synthesis
[chapter]
2016
Smart Innovation, Systems and Technologies
This paper presents a technique for spectral modeling using a deep neural network (DNN) for statistical parametric speech synthesis. In statistical parametric speech synthesis systems, spectrum is generally represented by low-dimensional spectral envelope parameters such as cepstrum and LSP, and the parameters are statistically modeled using hidden Markov models (HMMs) or DNNs. In this paper, we propose a statistical parametric speech synthesis system that models highdimensional spectral
doi:10.1007/978-3-319-28109-4_12
fatcat:oy2a773e5begpg7bmimipkyav4