Directly modeling voiced and unvoiced components in speech waveforms by neural networks

ICASSP, pp. 5640-5644, 2016.

Cited by: 33|Bibtex|Views10
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Other Links: dblp.uni-trier.de|academic.microsoft.com

Abstract:

This paper proposes a novel acoustic model based on neural networks for statistical parametric speech synthesis. The neural network outputs parameters of a non-zero mean Gaussian process, which defines a probability density function of a speech waveform given linguistic features. The mean and covariance functions of the Gaussian process r...More

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