MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis
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Cited by 49 in Diffusion models, but placed by its own abstract, which didn’t fit.
Abstract (arXiv)
Previous works (Donahue et al., 2018a; Engel et al., 2019a) have found that generating coherent raw audio waveforms with GANs is challenging. In this paper, we show that it is possible to train GANs reliably to generate high quality coherent waveforms by introducing a set of architectural changes and simple training techniques. Subjective evaluation metric (Mean Opinion Score, or MOS) shows the effectiveness of the proposed approach for high quality mel-spectrogram inversion. To establish the generality of the proposed techniques, we show qualitative results of our model in speech synthesis, music domain translation and unconditional music synthesis. We evaluate the various components of the model through ablation studies and suggest a set of guidelines to design general purpose discriminators and generators for conditional sequence synthesis tasks. Our model is non-autoregressive, fully convolutional, with significantly fewer parameters than competing models and generalizes to unseen speakers for mel-spectrogram inversion. Our pytorch implementation runs at more than 100x faster than realtime on GTX 1080Ti GPU and more than 2x faster than real-time on CPU, without any hardware specific optimization tricks.
Key facts. Cited by 354 papers in the map (data through 14 Oct 2026). First posted on arXiv 8 Oct 2019.
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Citing papers per year: 2020: 1; 2021: 88; 2022: 92; 2023: 56; 2024: 55; 2025: 45; 2026: 17.
354 papers.
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- 2020DiffWave: A Versatile Diffusion Model for Audio Synthesiscited by 1,354
- 2021SoundStream: An End-to-End Neural Audio Codeccited by 771
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50 most cited of 354 All 354 (JSON)
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50 newest of 354 All 354 (JSON)
- 2020DiffWave: A Versatile Diffusion Model for Audio Synthesiscited by 1,354
- 2021Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speechcited by 447
- 2022Diffsound: Discrete Diffusion Model for Text-to-sound Generationcited by 257
- 2022Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Qualitycited by 182
- 2023Diff-Foley: Synchronized Video-to-Audio Synthesis with Latent Diffusion Modelscited by 134
- 2021Guided-TTS: A Diffusion Model for Text-to-Speech via Classifier Guidancecited by 84
- 2024Detecting Multimedia Generated by Large AI Models: A Surveycited by 76
- 2022BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality Speech Synthesiscited by 64
- 2022Discrete Contrastive Diffusion for Cross-Modal Music and Image Generationcited by 44
- 2022DiffGAN-TTS: High-Fidelity and Efficient Text-to-Speech with Denoising Diffusion GANscited by 43
- 2022Multi-instrument Music Synthesis with Spectrogram Diffusioncited by 42
- 2022SpecGrad: Diffusion Probabilistic Model based Neural Vocoder with Adaptive Noise Spectral Shapingcited by 37
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- 2026Few-shot Acoustic Synthesis with Multimodal Flow Matching19 Mar 2026
- 2025Flow2GAN: Hybrid Flow Matching and GAN with Multi-Resolution Network for Few-step High-Fidelity Audio Generation29 Dec 2025
- 2025BridgeVoC: Revitalizing Neural Vocoder from a Restoration Perspective10 Nov 2025
- 2025Shortcut Flow Matching for Speech Enhancement: Step-Invariant flows via single stage training25 Sep 2025
- 2025Back to Ear: Perceptually Driven High Fidelity Music Reconstruction18 Sep 2025
- 2025LatentVoiceGrad: Nonparallel Voice Conversion with Latent Diffusion/Flow-Matching Models10 Sep 2025
- 2025DreamAudio: Customized Text-to-Audio Generation with Diffusion Models7 Sep 2025
- 2025WaveLLDM: Design and Development of a Lightweight Latent Diffusion Model for Speech Enhancement and Restoration28 Aug 2025
- 2025FasterVoiceGrad: Faster One-step Diffusion-Based Voice Conversion with Adversarial Diffusion Conversion Distillation25 Aug 2025
- 2025Learning to Upsample and Upmix Audio in the Latent Domain31 May 2025
- 2025Score Distillation Sampling for Audio: Source Separation, Synthesis, and Beyond7 May 2025
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- 2023High-Fidelity Audio Compression with Improved RVQGANcited by 431
- 2021Generative Spoken Language Modeling from Raw Audiocited by 340
- 2022AudioGen: Textually Guided Audio Generationcited by 295
- 2021Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Modelscited by 252
- 2022BigVGAN: A Universal Neural Vocoder with Large-Scale Trainingcited by 251
- 2021A Survey on Neural Speech Synthesiscited by 184
- 2022It's Raw! Audio Generation with State-Space Modelscited by 171
- 2023Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesiscited by 153
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- 2026GS-Codec: A Gaussian-Splatting Bottleneck for Neural Audio Coding3 Oct 2026
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- 2026Architecture and Affordances of PLAUD: Performative Latents and Unsupervised DDSP13 Aug 2026
- 2026OLIVE: View-Augmented Latent Prediction with Waveform Reconstruction for Speech SSL29 Jun 2026
- 2026Music Transcription with (Almost) No Supervision22 May 2026
- 2026Spectro-Temporal Modulation Representation Framework for Human-Imitated Speech Detection25 Apr 2026
- 2026AT-ADD: All-Type Audio Deepfake Detection Challenge Evaluation Plan9 Apr 2026
- 2026SqueezeComposer: Temporal Speed-up is A Simple Trick for Long-form Music Composing22 Mar 2026
- 2026MOSS-TTS Technical Report18 Mar 2026
- 2026Toward Complex-Valued Neural Networks for Waveform Generation12 Mar 2026
- 2026Reconstruct! Don't Encode: Self-Supervised Representation Reconstruction Loss for High-Intelligibility and Low-Latency Streaming Neural Audio Codec6 Mar 2026
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