Mar 14, 2019 · This paper proposes a framework of speech synthesis based on deep Gaussian processes (DGPs), which is a deep architecture model composed of stacked Bayesian ...
A framework of speech synthesis based on deep Gaussian processes (DGPs), which is a deep architecture model composed of stacked Bayesian kernel regressions, ...
Apr 4, 2019 · Abstract—This paper proposes a framework of speech synthesis based on deep Gaussian processes (DGPs), which is a deep architec-.
Statistical Parametric Speech Synthesis Using Deep Gaussian Processes ... Proposed method based on deep Gaussian processes.
Oct 22, 2024 · This paper proposes a statistical parametric speech synthesis technique based on Gaussian process regression (GPR).
This paper proposes deep Gaussian process (DGP)-based frameworks for multi-speaker speech synthesis and speaker representation learning.
In this paper, we evaluate a framework of statistical parametric speech synthesis based on Gaussian process regression (GPR) and compare it with those based ...
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Feb 27, 2024 · This paper presents a speech synthesis method based on the deep Gaussian process (DGP) and sequence-to-sequence (Seq2Seq) learning for high-quality, end-to-end ...
Experimental results show that the DNN-based systems outperformed the HMM-based systems with similar numbers of parameters. Index Terms— Statistical parametric ...
Missing: Gaussian | Show results with:Gaussian
Mar 26, 2021 · Abstract. This paper proposes deep Gaussian process (DGP)-based frameworks for multi-speaker speech synthesis and speaker representation.