Methods › Audio › Generative Audio Models › WaveGlow
WaveGlow
Introduced by Ryan Prenger et al. in WaveGlow: A Flow-based Generative Network for Speech Synthesis
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
WaveGlow is a flow-based generative model that generates audio by sampling from a distribution. Specifically samples are taken from a zero mean spherical Gaussian with the same number of dimensions as our desired output, and those samples are put through a series of layers that transforms the simple distribution to one which has the desired distribution.
Papers archive 2025-07-28
21 shown of 21, 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.
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Enhancing Kurdish Text-to-Speech with Native Corpus Training: A High-Quality WaveGlow Vocoder Approach 10 Sep 2024 · 0 repositories · arXiv:2409.13734
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Code-Mixed Text to Speech Synthesis under Low-Resource Constraints 2 Dec 2023 · 0 repositories · arXiv:2312.01103
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Rapid Speaker Adaptation in Low Resource Text to Speech Systems using Synthetic Data and Transfer learning 2 Dec 2023 · 0 repositories · arXiv:2312.01107
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Affective social anthropomorphic intelligent system 19 Apr 2023 · 0 repositories · arXiv:2304.11046
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Adaptive re-calibration of channel-wise features for Adversarial Audio Classification 21 Oct 2022 · 0 repositories · arXiv:2210.11722
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NatiQ: An End-to-end Text-to-Speech System for Arabic 15 Jun 2022 · 0 repositories · arXiv:2206.07373
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FlowVocoder: A small Footprint Neural Vocoder based Normalizing flow for Speech Synthesis 27 Sep 2021 · 0 repositories · arXiv:2109.13675
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Adaptation of Tacotron2-based Text-To-Speech for Articulatory-to-Acoustic Mapping using Ultrasound Tongue Imaging 26 Jul 2021 · 1 repository · arXiv:2107.12051
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A Flow-Based Neural Network for Time Domain Speech Enhancement 16 Jun 2021 · 0 repositories · arXiv:2106.09008
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Low Bit-Rate Wideband Speech Coding: A Deep Generative Model based Approach 4 Feb 2021 · 0 repositories · arXiv:2102.02640
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Text-to-speech for the hearing impaired 3 Dec 2020 · 0 repositories · arXiv:2012.02174
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MelGlow: Efficient Waveform Generative Network Based on Location-Variable Convolution 3 Dec 2020 · 3 repositories · arXiv:2012.01684
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StyleMelGAN: An Efficient High-Fidelity Adversarial Vocoder with Temporal Adaptive Normalization 3 Nov 2020 · 2 repositories · arXiv:2011.01557Syntology ran 0 of 2 samples · 2 unverified
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A comparison of Vietnamese Statistical Parametric Speech Synthesis Systems 26 May 2020 · 0 repositories · arXiv:2005.12962
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Probing the phonetic and phonological knowledge of tones in Mandarin TTS models 23 Dec 2019 · 1 repository · arXiv:1912.10915
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WaveFlow: A Compact Flow-based Model for Raw Audio 3 Dec 2019 · 4 repositories · arXiv:1912.01219Syntology ran 3 of 9 samples · 6 unverified
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Speaker independence of neural vocoders and their effect on parametric resynthesis speech enhancement 14 Nov 2019 · 0 repositories · arXiv:1911.06266
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Transferring neural speech waveform synthesizers to musical instrument sounds generation 27 Oct 2019 · 0 repositories · arXiv:1910.12381
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Parametric Resynthesis with neural vocoders 16 Jun 2019 · 1 repository · arXiv:1906.06762
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WaveCycleGAN2: Time-domain Neural Post-filter for Speech Waveform Generation 5 Apr 2019 · 0 repositories · arXiv:1904.02892
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WaveGlow: A Flow-based Generative Network for Speech Synthesis 31 Oct 2018 · 2 repositories · arXiv:1811.00002Syntology ran 2 of 7 samples · 5 unverified
Tasks archive 2025-07-28
20 shown of 23 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
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
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections