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Found 6 papers, 1 papers with code
Ensemble prosody prediction for expressive speech synthesis
Generating expressive speech with rich and varied prosody continues to be a challenge for Text-to-Speech.
ADEPT: A Dataset for Evaluating Prosody Transfer
Text-to-speech is now able to achieve near-human naturalness and research focus has shifted to increasing expressivity.
Ctrl-P: Temporal Control of Prosodic Variation for Speech Synthesis
Text does not fully specify the spoken form, so text-to-speech models must be able to learn from speech data that vary in ways not explained by the corresponding text.
Scattering Networks on the Sphere for Scalable and Rotationally Equivariant Spherical CNNs
Convolutional neural networks (CNNs) constructed natively on the sphere have been developed recently and shown to be highly effective for the analysis of spherical data.
Efficient Generalized Spherical CNNs
We develop two new strictly equivariant layers with reduced complexity $\mathcal{O}(CL^4)$ and $\mathcal{O}(CL^3 \log L)$, making larger, more expressive models computationally feasible.
Wavelet-Based Segmentation on the Sphere
Wavelets on the sphere have been developed to solve such problems for data defined on the sphere, which arise in numerous fields such as cosmology and geophysics.
