# Source-Filter HiFi-GAN: Fast and Pitch Controllable High-Fidelity Neural Vocoder

arXiv: https://arxiv.org/abs/2210.15533 · HTML: https://mlsanity.com/paper/2210.15533/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- Builds on 17 of its 31 references that are in the map.
- First posted on arXiv 27 Oct 2022.

## Builds on (most cited first, 17 of 17)

- [DiffWave: A Versatile Diffusion Model for Audio Synthesis](https://mlsanity.com/paper/2009.09761/) (2020)
- [HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis](https://mlsanity.com/paper/2010.05646/) (2020)
- [Least Squares Generative Adversarial Networks](https://mlsanity.com/paper/1611.04076/) (2016)
- [WaveGrad: Estimating Gradients for Waveform Generation](https://mlsanity.com/paper/2009.00713/) (2020)
- [Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech](https://mlsanity.com/paper/2106.06103/) (2021)
- [MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis](https://mlsanity.com/paper/1910.06711/) (2019)
- [UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation](https://mlsanity.com/paper/2106.07889/) (2021)
- [Neural source-filter waveform models for statistical parametric speech synthesis](https://mlsanity.com/paper/1904.12088/) (2019)
- [VISinger: Variational Inference with Adversarial Learning for End-to-End Singing Voice Synthesis](https://mlsanity.com/paper/2110.08813/) (2021)
- [StyleMelGAN: An Efficient High-Fidelity Adversarial Vocoder with Temporal Adaptive Normalization](https://mlsanity.com/paper/2011.01557/) (2020)
- [JETS: Jointly Training FastSpeech2 and HiFi-GAN for End to End Text to Speech](https://mlsanity.com/paper/2203.16852/) (2022)
- [Neural source-filter-based waveform model for statistical parametric speech synthesis](https://mlsanity.com/paper/1810.11946/) (2018)
- [Quasi-Periodic Parallel WaveGAN: A Non-autoregressive Raw Waveform Generative Model with Pitch-dependent Dilated Convolution Neural Network](https://mlsanity.com/paper/2007.12955/) (2020)
- [PeriodNet: A non-autoregressive waveform generation model with a structure separating periodic and aperiodic components](https://mlsanity.com/paper/2102.07786/) (2021)
- [Quasi-Periodic WaveNet: An Autoregressive Raw Waveform Generative Model with Pitch-dependent Dilated Convolution Neural Network](https://mlsanity.com/paper/2007.05663/) (2020)
- [Unified Source-Filter GAN with Harmonic-plus-Noise Source Excitation Generation](https://mlsanity.com/paper/2205.06053/) (2022)
- [Unified Source-Filter GAN: Unified Source-filter Network Based On Factorization of Quasi-Periodic Parallel WaveGAN](https://mlsanity.com/paper/2104.04668/) (2021)

## Built on by (most cited first, 11 of 11)

- [The Singing Voice Conversion Challenge 2023](https://mlsanity.com/paper/2306.14422/) (2023)
- [HierVST: Hierarchical Adaptive Zero-shot Voice Style Transfer](https://mlsanity.com/paper/2307.16171/) (2023)
- [PeriodGrad: Towards Pitch-Controllable Neural Vocoder Based on a Diffusion Probabilistic Model](https://mlsanity.com/paper/2402.14692/) (2024)
- [SiFiSinger: A High-Fidelity End-to-End Singing Voice Synthesizer based on Source-filter Model](https://mlsanity.com/paper/2410.12536/) (2024)
- [A Comparative Study of Voice Conversion Models with Large-Scale Speech and Singing Data: The T13 Systems for the Singing Voice Conversion Challenge 2023](https://mlsanity.com/paper/2310.05203/) (2023)
- [PitchFlower: A flow-based neural audio codec with pitch controllability](https://mlsanity.com/paper/2510.25566/) (2025)
- [VoiceDesigner: Text-to-Voice Generation and Editing via Unified Diffusion Modeling and Data Augmentation](https://mlsanity.com/paper/2608.13613/) (2026)
- [Compression of end-to-end non-autoregressive image-to-speech system for low-resourced devices](https://mlsanity.com/paper/2312.00174/) (2023)
- [BERT-APC: A Reference-free Framework for Automatic Pitch Correction via Musical Context Inference](https://mlsanity.com/paper/2511.20006/) (2025)
- [Vibrato Expression Control for Singing Voice Conversion with Improving Independent Control](https://mlsanity.com/paper/2606.17126/) (2026)
- [Investigating Human-Model Discrepancies in Speech Quality Assessment via Acoustic and Prosodic Perturbations](https://mlsanity.com/paper/2606.19951/) (2026)

## Abstract (arXiv)

Our previous work, the unified source-filter GAN (uSFGAN) vocoder, introduced a novel architecture based on the source-filter theory into the parallel waveform generative adversarial network to achieve high voice quality and pitch controllability. However, the high temporal resolution inputs result in high computation costs. Although the HiFi-GAN vocoder achieves fast high-fidelity voice generation thanks to the efficient upsampling-based generator architecture, the pitch controllability is severely limited. To realize a fast and pitch-controllable high-fidelity neural vocoder, we introduce the source-filter theory into HiFi-GAN by hierarchically conditioning the resonance filtering network on a well-estimated source excitation information. According to the experimental results, our proposed method outperforms HiFi-GAN and uSFGAN on a singing voice generation in voice quality and synthesis speed on a single CPU. Furthermore, unlike the uSFGAN vocoder, the proposed method can be easily adopted/integrated in real-time applications and end-to-end systems.