Data to 14 Oct 2026

Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram

arXiv 1910.11480 ↗First posted 25 Oct 2019eess.AS cs.LG cs.SDcited by 340

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Cited by 44 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We propose Parallel WaveGAN, a distillation-free, fast, and small-footprint waveform generation method using a generative adversarial network. In the proposed method, a non-autoregressive WaveNet is trained by jointly optimizing multi-resolution spectrogram and adversarial loss functions, which can effectively capture the time-frequency distribution of the realistic speech waveform. As our method does not require density distillation used in the conventional teacher-student framework, the entire model can be easily trained. Furthermore, our model is able to generate high-fidelity speech even with its compact architecture. In particular, the proposed Parallel WaveGAN has only 1.44 M parameters and can generate 24 kHz speech waveform 28.68 times faster than real-time on a single GPU environment. Perceptual listening test results verify that our proposed method achieves 4.16 mean opinion score within a Transformer-based text-to-speech framework, which is comparative to the best distillation-based Parallel WaveNet system.

Key facts. Cited by 340 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Oct 2019.

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Citing papers per year: 2020: 1; 2021: 77; 2022: 83; 2023: 54; 2024: 47; 2025: 39; 2026: 39.

340 papers.

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2020DiffWave: A Versatile Diffusion Model for Audio Synthesiscited by 1,354
2022High Fidelity Neural Audio Compressioncited by 687
2021Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speechcited by 447
2023High-Fidelity Audio Compression with Improved RVQGANcited by 431
2023Voicebox: Text-Guided Multilingual Universal Speech Generation at Scalecited by 379
2022AudioGen: Textually Guided Audio Generationcited by 295
2022BigVGAN: A Universal Neural Vocoder with Large-Scale Trainingcited by 251
2023Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Modelscited by 236
2021A Survey on Neural Speech Synthesiscited by 184
2021SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processingcited by 180
2022It's Raw! Audio Generation with State-Space Modelscited by 171
2021DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanismcited by 154

38 more

2022ProDiff: Progressive Fast Diffusion Model For High-Quality Text-to-Speechcited by 149
2021Deepfakes Generation and Detection: State-of-the-art, open challenges, countermeasures, and way forwardcited by 82
2021PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Priorcited by 80
2021WaveFake: A Data Set to Facilitate Audio Deepfake Detectioncited by 78
2022Universal Speech Enhancement with Score-based Diffusioncited by 75
2021RAVE: A variational autoencoder for fast and high-quality neural audio synthesiscited by 73
2022SQ-VAE: Variational Bayes on Discrete Representation with Self-annealed Stochastic Quantizationcited by 68
2021WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesiscited by 65
2021VQMIVC: Vector Quantization and Mutual Information-Based Unsupervised Speech Representation Disentanglement for One-shot Voice Conversioncited by 64
2022BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality Speech Synthesiscited by 64
2021StarGANv2-VC: A Diverse, Unsupervised, Non-parallel Framework for Natural-Sounding Voice Conversioncited by 58
2023Mega-TTS: Zero-Shot Text-to-Speech at Scale with Intrinsic Inductive Biascited by 51
2022Visual Acoustic Matchingcited by 45
2022A3T: Alignment-Aware Acoustic and Text Pretraining for Speech Synthesis and Editingcited by 40
2021Neural Dubber: Dubbing for Videos According to Scriptscited by 39
2022SpecGrad: Diffusion Probabilistic Model based Neural Vocoder with Adaptive Noise Spectral Shapingcited by 37
2021Bilateral Denoising Diffusion Modelscited by 36
2022Emotion Intensity and its Control for Emotional Voice Conversioncited by 35
2022SVTS: Scalable Video-to-Speech Synthesiscited by 35
2022An Overview of Affective Speech Synthesis and Conversion in the Deep Learning Eracited by 33
2022iSTFTNet: Fast and Lightweight Mel-Spectrogram Vocoder Incorporating Inverse Short-Time Fourier Transformcited by 32
2024The Codecfake Dataset and Countermeasures for the Universally Detection of Deepfake Audiocited by 31
2023Controllable Music Production with Diffusion Models and Guidance Gradientscited by 29
2021LightSpeech: Lightweight and Fast Text to Speech with Neural Architecture Searchcited by 28
2022InferGrad: Improving Diffusion Models for Vocoder by Considering Inference in Trainingcited by 28
2022textless-lib: a Library for Textless Spoken Language Processingcited by 28
2023Intelligible Lip-to-Speech Synthesis with Speech Unitscited by 28
2021End-to-End Video-To-Speech Synthesis using Generative Adversarial Networkscited by 27
2023Imaginary Voice: Face-styled Diffusion Model for Text-to-Speechcited by 27
2022JETS: Jointly Training FastSpeech2 and HiFi-GAN for End to End Text to Speechcited by 26
2021Universal Neural Vocoding with Parallel WaveNetcited by 25
2023VITS2: Improving Quality and Efficiency of Single-Stage Text-to-Speech with Adversarial Learning and Architecture Designcited by 25
2021Fre-GAN: Adversarial Frequency-consistent Audio Synthesiscited by 24
2024Towards Controllable Speech Synthesis in the Era of Large Language Models: A Systematic Surveycited by 23
2021ESPnet2-TTS: Extending the Edge of TTS Researchcited by 22
2023Miipher: A Robust Speech Restoration Model Integrating Self-Supervised Speech and Text Representationscited by 22
2023Physics-Driven Diffusion Models for Impact Sound Synthesis from Videoscited by 22
2023A Representative Study on Human Detection of Artificially Generated Media Across Countriescited by 22

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