Methods › Audio › Text-to-Speech Models › ParaNet

ParaNet

4 papers tagged archive 2025-07-28

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

ParaNet is a non-autoregressive attention-based architecture for text-to-speech, which is fully convolutional and converts text to mel spectrogram. ParaNet distills the attention from the autoregressive text-to-spectrogram model, and iteratively refines the alignment between text and spectrogram in a layer-by-layer manner. The architecture is otherwise similar to Deep Voice 3 except these changes to the decoder; whereas the decoder of DV3 has multiple attention-based layers, where each layer consists of a causal convolution block followed by an attention block, ParaNet has a single attention block in the encoder.

Source: Non-Autoregressive Neural Text-to-Speech

Papers archive 2025-07-28

4 shown of 4, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Estimating Parameters of the Tree Root in Heterogeneous Soil Environments via Mask-Guided Multi-Polarimetric Integration Neural Network
27 Dec 2021 · 0 repositories · arXiv:2112.13494
ParaNet: Deep Regular Representation for 3D Point Clouds
5 Dec 2020 · 0 repositories · arXiv:2012.03028
Parallel Neural Text-to-Speech
1 Jan 2020 · 0 repositories
Non-Autoregressive Neural Text-to-Speech
21 May 2019 · 2 repositories · arXiv:1905.08459

Syntology ran 2 of 7 samples · 5 unverified

Tasks archive 2025-07-28

5 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

Task	Papers
Text to Speech	2
text-to-speech	2
GPR	1
Text-To-Speech Synthesis	1
point cloud upsampling	1

Usage over time archive 2025-07-28

Papers per year the archive tags with this method, by the paper's archive date (4 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Text-to-Speech Models

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